Methods for predicting anti-cancer response

ABSTRACT

The present invention is based, in part, on the identification of novel methods for defining predictive biomarkers of response to anti-cancer drugs.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 14/466,208 filed Aug. 22, 2014, which is acontinuation application of International Application No. PCT/US13/27295filed Feb. 22, 2013, which claims benefit under 35 U.S.C. 119(e) of U.S.provisional applications No. 61/602,460 filed Feb. 23, 2012, and61/604,810 filed Feb. 29, 2012, the contents of which are incorporatedherein by reference in their entirety.

GOVERNMENT SUPPORT

This invention was made with government support under grant numberCA089393097193 awarded by National Institutes of Health. The Governmenthas certain rights in the invention.

BACKGROUND OF THE INVENTION

Medical oncologists have benefited greatly from relatively recentefforts to dissect and understand the genetic elements underlyingmammalian cancer. The identification of specific geneticpredispositions, such as mutations in BRCA-1, BRCA2, and HER2, hasprovided key insights into the mechanisms underlying tumorigenesis andhas proven useful for the design of new generations of targetedapproaches for clinical intervention. With the determination of thehuman genome sequence and improvements in sequencing and bioinformaticstechnologies, systematic analyses of genetic alterations in humancancers have become possible.

However, clinical interventions based upon this information have beenseverely hampered by the fact that often only a percentage of patientswill respond favorably to a particular anti-cancer treatment. Medicaloncologists currently cannot generally predict which patients will orwill not respond to a proposed chemotherapeutic treatment.

Accordingly, there is a great need in the art to identify patientresponsiveness to particular anti-cancer therapies.

SUMMARY OF THE INVENTION

The present invention is based, at least in part, on the discovery thatcertain patterns of DNA aberrations described herein are predictive ofanti-cancer response of the cells harboring such DNA aberrations toanti-cancer therapies.

Accordingly, in one aspect, the present invention features a method forpredicting the outcome of anti-cancer treatment of a subject with a cellhyperproliferative disorder, comprising determining a global chromosomalaberration score (GCAS), comprising obtaining a biological sample fromthe subject and determining whether a plurality of chromosomal regionsdisplaying a chromosomal aberration exists within a plurality ofchromosomal loci, wherein said chromosomal aberrations are selected fromthe group consisting of allelic imbalance (AI), loss of heterozygosity(LOH), copy number aberrations (CNA), copy number gain (CNG), copynumber decrease (CND) and combinations thereof, relative to a control,and wherein the presence of a plurality of chromosomal regionsdisplaying said chromosomal aberrations predicts the outcome ofanti-cancer treatment of the subject. The subject can be a mammal, suchas a human.

For example, mutations in BRCA1 or BRCA2 cause defects in DNA repairthat predict sensitivity to platinum salts in breast and ovarian cancer;however, some patients without BRCA mutations also benefit from theseagents. This study shows that defects in DNA repair that cause platinumsensitivity can be inferred from the number of allelic imbalance (AI) orthe number of telomeric allelic imbalance (NtAI), a measure of genomicaberration in tumors. NtAI may identify cancer patients without BRCAmutations who are likely to benefit from platinum-based therapy.

In one aspect, the anti-cancer treatment is chemotherapy treatment. Inanother embodiment, the anti-cancer treatment comprises platinum-basedchemotherapeutic agents (e.g., cisplatin, carboplatin, oxaliplatin,nedaplatin, and iproplatin).

In another aspect, the cell hyperproliferative disorder is selected fromthe group consisting of breast cancer, ovarian cancer, transitional cellbladder cancer, bronchogenic lung cancer, thyroid cancer, pancreaticcancer, prostate cancer, uterine cancer, testicular cancer, gastriccancer, soft tissue and osteogenic sarcomas, neuroblastoma, Wilms'tumor, malignant lymphoma (Hodgkin's and non-Hodgkin's), acutemyeloblastic leukemia, acute lymphoblastic leukemia, Kaposi's sarcoma,Ewing's tumor, refractory multiple myeloma, and squamous cell carcinomasof the head, neck, cervix, and vagina.

In still another aspect, the biological sample is selected from thegroup consisting of cells, cell lines, histological slides, frozen corebiopsies, paraffin embedded tissues, formalin fixed tissues, biopsies,whole blood, nipple aspirate, serum, plasma, buccal scrape, saliva,cerebrospinal fluid, urine, stool, and bone marrow. In one embodiment,the biological sample is enriched for the presence of hyperproliferativecells to at least 75% of the total population of cells. In anotherembodiment, the enrichment is performed according to at least onetechnique selected from the group consisting of needle microdissection,laser microdissection, fluorescence activated cell sorting, andimmunological cell sorting. In still another embodiment, an automatedmachine performs the at least one technique to thereby transform thebiological sample into a purified form enriched for the presence ofhyperproliferative cells. IN yet another embodiment, the biologicalsample is obtained before the subject has received adjuvantchemotherapy. Alternatively, the biological sample is obtained after thesubject has received adjuvant chemotherapy.

In yet another aspect, the control is determined from a non-cellhyperproliferative cell sample from the patient or member of the samespecies to which the patient belongs. In one embodiment, the control isdetermined from the average frequency of genomic locus appearance ofchromosomal regions of the same ethnic group within the species to whichthe patient belongs. In another embodiment, the control is fromnon-cancerous tissue that is the same tissue type as said canceroustissue of the subject. In still another embodiment, the control is fromnon-cancerous tissue that is not the same tissue type as said canceroustissue of the subject.

In another aspect, AI is determined using major copy proportion (MCP).In one embodiment, AI for a given genomic region is counted when MCP isgreater than 0.70.

In still another aspect, the plurality of chromosomal loci are randomlydistributed throughout the genome at least every 100 Kb of DNA. In oneembodiment, the plurality of chromosomal loci comprise at least onechromosomal locus on each of the 23 human chromosome pairs. In anotherembodiment, the plurality of chromosomal loci comprise at least onechromosomal locus on each arm of each of the 23 human chromosome pairs.In still another embodiment, the plurality of chromosomal loci compriseat least one chromosomal locus on at least one telomere of each of the23 human chromosome pairs. In yet another embodiment, the plurality ofchromosomal loci comprise at least one chromosomal locus on eachtelomere of each of the 23 human chromosome pairs.

In yet another aspect, the chromosomal aberrations have a minimumsegment size of at least 1 Mb. In one embodiment, the chromosomalaberrations have a minimum segment size of at least 12 Mb.

In another aspect, the plurality of chromosomal aberrations comprises atleast 5 chromosomal aberrations. In one embodiment, the plurality ofchromosomal aberrations comprises at least 13 chromosomal aberrations.

In still another aspect, the chromosomal loci are selected from thegroup consisting of single nucleotide polymorphisms (SNPs), restrictionfragment length polymorphisms (RFLPs), and simple tandem repeats (STRs).

In yet another aspect, the chromosomal loci are analyzed using at leastone technique selected from the group consisting of molecular inversionprobe (MIP), single nucleotide polymorphism (SNP) array, in situhybridization, Southern blotting, array comparative genomichybridization (aCGH), and next-generation sequencing.

In another aspect, the outcome of treatment is measured by at least onecriteria selected from the group consisting of survival until mortality,pathological complete response, semi-quantitative measures of pathologicresponse, clinical complete remission, clinical partial remission,clinical stable disease, recurrence-free survival, metastasis freesurvival, disease free survival, circulating tumor cell decrease,circulating marker response, and RECIST criteria.

In still another aspect, the method further comprises determining asuitable treatment regimen for the subject. In one embodiment, thesuitable treatment regimen comprises at least one platinum-basedchemotherapeutic agent when a plurality of genomic chromosomalaberrations is determined or does not comprise at least oneplatinum-based chemotherapeutic agent when no plurality of genomicchromosomal aberrations is determined.

The invention also provides an assay, such as an assay or a method forselecting therapy for a subject having cancer, the assay comprising:subjecting a biological sample comprising a cancer cell or nucleic acidfrom a cancer cell taken from the subject to telomeric allelic imbalance(tAI) analysis; detecting the number of telomeric allelic imbalance(NtAI) in the cancer cell or nucleic acid from the cancer cell, andselecting a platinum-comprising therapy for the subject when the NtAI isdetected to be above a reference value based on the recognition thatplatinum-comprising therapy is effective in patients who have NtAI abovethe reference value; and selecting a non-platinum-comprising cancertherapy for the subject when the NtAI is detected to be below areference value based on the recognition that platinum-comprising cancertherapy is not effective in patients who have the NtAI below a referencevalue, and optionally administering to the subject, such as a humansubject, the selected therapy.

An assay or a method for selecting platinum-comprising therapy for asubject having cancer comprising: subjecting a biological sample takenfrom the subject to allelic imbalance (AI) analysis; detecting thenumber of AI; and selecting platinum-comprising cancer therapy for thesubject when the number of AIs is above a reference value based on therecognition that platinum-comprising cancer therapy is effective inpatients who have the number of AIs is above a reference value, andoptionally administering the platinum-comprising cancer therapy if it isselected.

The assays may optionally comprise the steps of obtaining a samplecomprising cancer cells or cancer cell-derived DNA from the subject,subjecting the sample to manipulations, such as purification, DNAamplification, contacting the sample with a probe, labeling and othersuch steps that are needed in analysis of the NtAI or NAI. Moreover, theassaying and analysis may be performed by a non-human machine executingan algorithm and determining automatically whether the sample comprisesthe conditions to select a platinum-comprising cancer therapy ornon-platinum comprising cancer therapy to the subject based on theanalysis of NAI or NtAI.

The cancer may be any cancer. In some aspects of all the embodiments ofthe invention, the cancer is selected from breast and ovarian cancers.In some aspects of all the embodiments of the invention, the subject isnegative for the well-known BRCA1 and/or BRCA2 mutations. In someaspects of all the embodiments, the subject has decrease or increase inBRCA1 and/or BRCA2 mRNA, which may be optionally determined togetherwith the assay or before or after performing the assay, and which mayfurther assist in determining whether the cancer will be responsive orresistant to treatment with platinum-comprising cancer therapy.

We also provide a method for predicting the outcome of anti-cancertreatment of a subject with a cell hyperproliferative disorder,comprising determining a global chromosomal aberration score (GCAS),comprising obtaining a biological sample from the subject anddetermining whether a plurality of chromosomal regions displaying achromosomal aberration exists within a plurality of chromosomal loci,wherein said chromosomal aberrations are selected from the groupconsisting of allelic imbalance (NAI), loss of heterozygosity (NLOH),copy number aberrations (NCNA), copy number gain (NCNG), copy numberdecrease (NCND) and combinations thereof, relative to a control, andwherein the presence of a plurality of chromosomal regions displayingsaid chromosomal aberrations predicts the outcome of anti-cancertreatment of the subject.

We also provide a method for predicting the outcome of anti-cancertreatment of a subject with a cell hyperproliferative disorder,comprising determining a global chromosomal aberration score (GCAS),comprising obtaining a biological sample from the subject anddetermining whether a plurality of chromosomal regions displaying achromosomal aberration exists within a plurality of chromosomal loci,wherein said chromosomal aberrations are selected from the groupconsisting of allelic imbalance (NAI), loss of heterozygosity (NLOH),copy number aberrations (NCNA), copy number gain (NCNG), copy numberdecrease (NCND) and combinations thereof, relative to a control, andwherein the presence of a plurality of chromosomal regions displayingsaid chromosomal aberrations predicts the outcome of anti-cancertreatment of the subject.

We further provide a method of determining prognosis in a patientcomprising: (a) determining whether the patient comprises cancer cellshaving an LOH signature, wherein the presence of more than a referencenumber of LOH regions in at least one pair of human chromosomes of acancer cell of the cancer patient that are longer than a first lengthbut shorter than the length of the whole chromosome containing the LOHregion indicates that the cancer cells have the LOH signature, whereinthe at least one pair of human chromosomes is not a human X/Y sexchromosome pair, wherein the first length is about 1.5 or moremegabases, and (b) (1) determining, based at least in part on thepresence of the LOH signature, that the patient has a relatively goodprognosis, or (b)(2) determining, based at least in part on the absenceof the LOH signature, that the patient has a relatively poor prognosis

We provide a composition comprising a therapeutic agent selected fromthe group consisting of DNA damaging agent, anthracycline, topoisomeraseI inhibitor, and PARP inhibitor for use in treating a cancer selectedfrom the group consisting of breast cancer, ovarian cancer, livercancer, esophageal cancer, lung cancer, head and neck cancer, prostatecancer, colon cancer, rectal cancer, colorectal cancer, and pancreaticcancer in a patient with more than a reference number of LOH regions inat least one pair of human chromosomes of a cancer cell of the patientthat are longer than a first length but shorter than the length of thewhole chromosome containing the LOH region, wherein the at least onepair of human chromosomes is not a human X/Y sex chromosome pair,wherein the first length is about 1.5 or more megabases.

We further provide a method of treating cancer in a patient, comprising:(a) determining in a sample from said patient the number of LOH regionsin at least one pair of human chromosomes of a cancer cell of the cancerpatient that are longer than a first length but shorter than the lengthof the whole chromosome containing the LOH region indicates that thecancer cells have the LOH signature, wherein the at least one pair ofhuman chromosomes is not a human X/Y sex chromosome pair, wherein thefirst length is about 1.5 or more megabases; (b) providing a test valuederived from the number of said LOH regions; (c) comparing said testvalue to one or more reference values derived from the number of saidLOH regions in a reference population (e.g., mean, median, terciles,quartiles, quintiles, etc.); and (d) administering to said patient ananti-cancer drug, or recommending or prescribing or initiating atreatment regimen comprising chemotherapy and/or a synthetic lethalityagent based at least in part on said comparing step revealing that thetest value is greater (e.g., at least 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or10-fold greater; at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standarddeviations greater) than at least one said reference value; or (e)recommending or prescribing or initiating a treatment regimen notcomprising chemotherapy and/or a synthetic lethality agent based atleast in part on said comparing step revealing that the test value isnot greater (e.g., not more than 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or10-fold greater; not more than 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standarddeviations greater) than at least one said reference value.

The method of Claim 33, wherein said DNA damaging agent is cisplatin,carboplatin, oxalaplatin, or picoplatin, said anthracycline isepirubincin or doxorubicin, said topoisomerase I inhibitor iscampothecin, topotecan, or irinotecan, and/or said PARP inhibitor isiniparib, olaparib or velapirib.

We provide a composition comprising a therapeutic agent selected fromthe group consisting of platinum comprising cancer therapy andanthracycline for use in treating a cancer selected from the groupconsisting of breast cancer, ovarian cancer, liver cancer, esophagealcancer, lung cancer, head and neck cancer, prostate cancer, coloncancer, rectal cancer, colorectal cancer, and pancreatic cancer in apatient with increased allelic imbalance.

We provide a method for predicting the outcome of anti-cancer treatmentof a subject with a cell hyperproliferative disorder, comprisingdetermining a global chromosomal aberration score (GCAS), comprisingobtaining a biological sample from the subject and determining whether aplurality of chromosomal regions displaying a chromosomal aberrationexists within a plurality of chromosomal loci, wherein said chromosomalaberrations are selected from the group consisting of allelic imbalance(NAI), loss of heterozygosity (NLOH), copy number aberrations (NCNA),copy number gain (NCNG), copy number decrease (NCND) and combinationsthereof, relative to a control, and wherein the presence of a pluralityof chromosomal regions displaying said chromosomal aberrations predictsthe outcome of anti-cancer treatment of the subject. In some aspects ofall the embodiments of the invention, the anti-cancer treatment ischemotherapy treatment, which may also be platinum-basedchemotherapeutic agents, for example, cisplatin, carboplatin,oxaliplatin, nedaplatin, and iproplatin.

In some aspects of all the embodiments of the invention, the cellhyperproliferative disorder can be selected from the group consisting ofbreast cancer, ovarian cancer, transitional cell bladder cancer,bronchogenic lung cancer, thyroid cancer, pancreatic cancer, prostatecancer, uterine cancer, testicular cancer, gastric cancer, soft tissueand osteogenic sarcomas, neuroblastoma, Wilms' tumor, malignant lymphoma(Hodgkin's and non-Hodgkin's), acute myeloblastic leukemia, acutelymphoblastic leukemia, Kaposi's sarcoma, Ewing's tumor, refractorymultiple myeloma, and squamous cell carcinomas of the head, neck,cervix, colon cancer, melanoma, and vagina.

The biological sample can be selected from the group consisting ofcells, cell lines, histological slides, frozen core biopsies, paraffinembedded tissues, formalin fixed tissues, biopsies, whole blood, nippleaspirate, serum, plasma, buccal scrape, saliva, cerebrospinal fluid,urine, stool, and bone marrow, wherein the sample comprises cancercells.

In some aspect of all the embodiments of the invention, including theassays and methods, the cancer cells in the sample may be enrichedusing, for example, needle microdissection, laser microdissection,fluorescence activated cell sorting, and immunological cell sorting.

In some aspects of all the embodiments of the invention an automatedmachine performs the at least one technique to thereby transform thebiological sample into a purified form enriched for the presence ofhyperproliferative cells.

In some aspects of all the embodiments of the invention, the sample orbiological sample is obtained before the subject has received adjuvantchemotherapy, or after the subject has received adjuvant chemotherapy.

In some aspects of all the embodiments of the invention, the control isdetermined from the average frequency of genomic locus appearance ofchromosomal regions of the same ethnic group within the species to whichthe patient belongs. The control may also be from non-cancerous tissuethat is the same tissue type as said cancerous tissue of the subject, orfrom non-cancerous tissue that is not the same tissue type as saidcancerous tissue of the subject.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1C show the correlation between allelic imbalance (AI) regionsand cisplatin sensitivity in vitro. FIG. 1A shows a dose response curvesof six TNBC cell lines as determined by a proliferation assay after 48hours of cisplatin exposure. Curves for cells with lower IC50 values(greater sensitivity) are shown in blue; the cell line with highest IC50(greatest resistance) is shown in red; cell lines with intermediatesensitivity are shown in grey. FIG. 1B shows the effect of the AIsegment size threshold on the correlation between the number oftelomeric AI regions and the cisplatin sensitivity in the six celllines. Each point represent an R2 value based on linear regressionbetween the count of CNA regions of a minimum size indicated at X-axis,and cisplatin IC₅₀ in a panel of 6 TNBC cell lines (BT20, BT-549,HCC1187, HCC38, MDA-MB-231, MDA-MB-468). The optimum minimum segmentsize threshold is indicated by the dotted line. FIG. 1C shows acomparison between the number of telomeric AI regions (NtAI,12) andcisplatin sensitivity at the selected optimum threshold of 12 Mb. Thecell lines are indicated as follows: 1, BT-20; 2, BT-549; 3, HCC1187; 4,HCC38; 5, MDA-MB-231; 6, MDA-MB-468.

FIG. 2 shows that major copy proportion (MCP) analysis identifiesallelic imbalance in tumor biopsy samples with different degrees oftumor cell purity. FIG. 2 shows the formula for calculation of MCP, aswell as normal bi-allelic chromosomes and three different ways in whichallelic imbalance of a chromosomal region may occur and thecorresponding MCP calculation. We also prepared diagrams depicting thedisplay of loss of heterozygosity (LOH), AI determined by MCP, andabsolute copy number analysis in two tumor samples with differentdegrees of normal cell contamination: T7 with >95% tumor cell contentand T5 with approximately 80% tumor content. The chromosomes areindicated along the left side. The first columns for each tumor show thecells for LOH (blue) and retention of heterozygosity (yellow) at eachchromosome position. The second columns show the MCP levels (between 0.5and 1.0) at each chromosomal position. The MCP cut off of 0.7 isindicated by red lines. AI is called for regions with MCP greater than0.7. The third and forth columns display the absolute DNA copy number ateach position with white indicating diploid, shades of red indicatingcopy gain and shades of blue indicating copy loss. The copy numberlevels are shown in the far right panels. The tumor sample with greaterpurity (T7) shows agreement between LOH and MCP-determined AI calls. Inthe tumor sample with only 80% tumor cells, the LOH signal is lost, butAI can still be estimated by MCP with a 0.70 threshold.

FIGS. 3A-3D show the association between cisplatin sensitivity andnumber of genomic abnormalities in a panel of TNBC cell lines. FIG. 3Ashows cisplatin IC50 versus number of telomeric AI regions at least 1 Mblong with AI defined by MCP>0.7. FIG. 3B shows cisplatin IC50 versuscount of regions with copy number aberration, including gains andlosses, at least 1 Mb long. FIG. 3C shows cisplatin IC50 versus count ofregions with copy number gain, at least 1 Mb long. FIG. 3D showscisplatin IC50 versus count of regions with copy number loss, at least 1Mb long. The cell lines are indicated on each figure and are the same asin FIG. 1.

FIGS. 4A-4B show the association between cisplatin sensitivity and countof either telomeric or interstitial AI regions in a panel of TNBC celllines. FIG. 4A shows cisplatin IC50 versus number of telomeric AIregions at least 1 Mb long with AI defined by MCP>0.7. FIG. 4B showscisplatin IC50 versus number of interstitial AI regions at least 1 Mblong with AI defined by MCP>0.7. The cell lines are indicated on eachfigure and are the same as in FIG. 1.

FIGS. 5A-5F show the association between enumerated copy numberaberrations (CNA) and sensitivity to cisplatin in vitro. FIGS. 5A-5Cshow the determination of the minimum segment size that demonstrates thebest correlation to cisplatin sensitivity for number of copy numberaberrations (NCNA; FIG. 5A), number of regions with copy number gain(NCNA, gain; FIG. 5B), and number of regions with copy number loss(NCNA, loss; FIG. 5C). Each point represent an R2 value based on linearregression between the count of CNA regions of a minimum size indicatedat X-axis, and cisplatin IC50 in a panel of 6 TNBC cell lines (BT20,BT-549, HCC1187, HCC38, MDA-MB-231, MDA-MB-468). The optimal minimumsize of CNA regions is indicated by the dotted line. FIG. 5D-5F showplots of the cisplatin IC50 values (μM, X-axis) vs. the number of CNAregions with optimum minimum segment sizes (Y-axis) as follows: NCNA atleast 9 Mb long (FIG. 5D), NCNA, gain at least 9 Mb long (FIG. 5E), andNCNA, loss at least 5 Mb long, in 6 TNBC cell lines (FIG. 5F), asindicated.

FIGS. 6A-6C show AI regions and cisplatin response in breast cancer.Pathologic response to cisplatin was assessed by the Miller-Payne (MP)score, which can range from 0 (progression) to 5 (pathologic completeresponse, pCR). FIG. 6A shows representations of individual tumorgenomes arranged in order of increasing MP score. Regions of telomericAI (dark blue) and interstitial AI (light blue) are indicated, with thinwhite lines demarcating individual chromosomes. FIG. 6B showsassociation between the MP score and the NtAI,12. FIG. 6C shows areceiver operating characteristics (ROC) curve evaluating theperformance of NtAI,12 to predict pCR to cisplatin therapy (pCR, n=4; nopCR, n=20).

FIG. 7 shows whole chromosome allelic imbalance (isodisomy) andcisplatin sensitivity in breast cancers. Regions of whole chromosome AIare indicated in red for each chromosomal location. Each row defined bythin white lines represents a different chromosome and chromosomenumbers are indicated along the left side. Each column represents anindividual tumor sample. The Miller-Payne (MP) pathologic response scorefor each tumor is indicated along the bottom. Cases are arranged inorder of increasing pathologic response to cisplatin (0=progression,5=pathologic complete response (pCR)).

FIGS. 8A-8B show AI regions and time to relapse in serous ovarian cancertreated with platinum based therapy. FIG. 8A shows a rank of individualsaccording to increasing NtAI,12. Those who relapsed within one year areindicated by closed circles and those without relapse within one yearare indicated by open circles. A cutoff value of NtAI,12=13, based onthe TNBC ROC analysis for prediction of pathologic complete response(pCR) to cisplatin, is indicated by the dotted line. FIG. 8B showsKaplan-Meier survival curves for time to relapse in individualsclassified as high NtAI,12 (13 or greater NtAI,12 regions, blue) or lowNtAI,12 (fewer than 13 NtAI,12 regions, red).

FIG. 9 shows a model relating DNA repair to accumulation of AI andresponse to platinum agents. Various genetic lesions can result indefects in common pathways of DNA repair, leading first to abnormalrepair of spontaneous DNA breaks, then to illegitimate chromosomerecombination and aberrant quadriradial chromosome formation, andfinally to high levels of telomeric allelic imbalance. In parallel, thedefective DNA repair pathway can also result in the inability of thetumor cell to repair drug-induced DNA damage, leading to tumorsensitivity to drugs such as platinum salts. Thus, the level oftelomeric AI in a tumor serves as an indicator of defective DNA repairand predicts sensitivity to treatment with genotoxic agents.

FIGS. 10A-10C show chromosomal aberrations and cisplatin sensitivity invitro. The relationship between AI regions and cisplatin sensitivity wasanalyzed in 10 breast cancer cell lines: 1: CAMA-1, 2: HCC1954,3:MDA-MB-231, 4: MDA-MB-361, 5: HCC1187, 6:BT-549,7: HCC1143, 8:MDA-MB-468, 9: BT-20, 10: T47D. FIG. 10A shows IC₅₀ values for each ofthe 10 cell lines. A proliferation assay was used to assess viabilityafter 48 hours of cisplatin exposure and IC₅₀ was determined from thedose response curves. FIG. 10B shows comparison between number ofregions with telomeric allelic imbalance (NtAI) and cisplatinsensitivity. Breast cancer subtype is indicated as follows: TN, red;HER2+, green, ER+HER2−, blue. FIG. 10C shows comparison between (NtAI)and cisplatin sensitivity as determined by GI50 in breast cancer celllines from Heiser et al. (18). Reported transcriptional subtype isindicated as follows: basal, red; claudin-low, pink; ERBB2Amp, green;luminal, blue.

FIGS. 11A-11D show an NtAI and cisplatin response in breast cancer. Intwo clinical trials, TNBC patients were given preoperative cisplatin(Cisplatin-1, FIG. 11A-11B) or cisplatin and bevacizumab (Cisplatin-2,FIG. 11C-11D). Cisplatin sensitive tumors are indicated in red,cisplatin insensitive tumors are indicated in black. Tumors withgermline mutations in BRCA1/2 are indicated with triangles. FIG. 11A andFIG. 11C show box plots showing NtAI distribution in cisplatin resistantand sensitive tumors. FIG. 11B and FIG. 11D show Receiver operatingcharacteristic curves showing the ability of NtAI to predict forsensitivity to cisplatin.

FIG. 12 shows NtAI and cisplatin response in serous ovarian cancer. Boxplots showing NtAI distribution in platinum sensitive and resistanttumors in cancers without BRCA1 or BRCA2 mutations (wtBRCA) and forcancers with germline or somatic mutation in BRCA1 (mBRCA1) or in BRCA2(mBRCA2). Red indicate sensitive samples, triangles indicate sampleswith germline or somatic mutations in BRCA1 or BRCA2. Significantdifferences between resistant wtBRCA and sensitive groups are indicated.In addition, significant differences were found between sensitive wtBRCAand sensitive mBRCA2 (P=0.047), and sensitive wtBRCA and sensitivemBRCA1 (P=0.014).

FIGS. 13A-13B show enrichment of common CNVs in tAI chromosomalbreakpoints from TNBC. Association of tAI breakpoints with common CNVloci based on computational simulations that compared the expectednumber of breakpoints containing CNVs with the observed number in totalcases in Cisplatin-1 (FIG. 13A) and Cisplatin-2 (FIG. 13B).

FIGS. 14A-14C show Association between BRCA1 expression, NtAI and BRCA1promoter methylation. Red indicates tumors sensitive to cisplatin.Tumors with a germline mutation in BRCA1 or BRCA2 are excluded in FIG.14A. and 14B, but included in 14C, represented as triangles. FIG. 14Ashows BRCA1 expression measured by qPCR is significantly lower insensitive tumors in the Cisplatin-2 cohort. FIG. 14B shows BRCA1expression is lower in samples that show methylation of the BRCA1promoter region in the combined Cisplatin-1 and Cisplatin-2 cohorts.FIG. 14C shows BRCA1 expression measured by qPCR shows a negativecorrelation with NtAI in the combined Cisplatin-1 and Cisplatin-2cohorts.

FIGS. 15A-15D show a model relating DNA repair to accumulation oftelomeric AI and response to platinum agents. FIG. 15A shows in DNArepair-competent cells, DNA breaks are repaired using error-freehomologous recombination employing the identical sister chromatid as atemplate, resulting in no AI. FIG. 15B and FIG. 15C show compromised DNArepair favors the use of error-prone repair pathways, resulting inchromosome rearrangements and aberrant radial chromosome formation.After mitotic division, daughter cells will have imbalance in theparental contribution of telomeric segments of chromosomes (telomericAI). FIG. 15B shows non-homologous end joining is one error-pronemechanism that joins a broken chromatid of one chromosome (dark blue) tothe chromatid of another, usually non-homologous, chromosome (white).Mitotic segregation results in cells with telomeric AI due tomono-allelic change in DNA copy number of the affected telomeric region.FIG. 15C shows mitotic recombination may result in rearrangementsbetween homologous chromosomes (dark blue and light blue). Mitoticsegregation results in cells with AI due to copy neutral LOH.Break-induced replication would be expected to result in a similaroutcome. FIG. 15D shows the same compromise in DNA repair that causestelomeric AI may also result in the inability of the tumor cell torepair drug-induced DNA damage, leading to tumor sensitivity to drugssuch as platinum salts.

FIG. 16 shows an example definition of allelic imbalance. The diagramshows normal bi-allelic chromosomes and three different ways in whichallelic imbalance of a chromosomal region may occur.

FIGS. 17A-17C show association between cisplatin sensitivity andmeasures of genomic abnormalities in a panel of breast cancer celllines. Cisplatin IC₅₀ versus: FIG. 17A, total number of AI regions; FIG.17B, total number of copy number gain regions; and FIG. 17C, totalnumber of copy number loss regions. Numbers represents the same celllines as in FIG. 1.

FIGS. 18A-18E show association between cisplatin sensitivity andtelomeric/interstitial gains and losses. Cisplatin IC₅₀ versus: FIG.18A, the number of telomeric copy number gain regions; FIG. 18B, thenumber of telomeric copy number loss regions; FIG. 18C, the number ofinterstitial copy number gain regions; FIG. 18D, the number ofinterstitial copy number loss regions; and FIG. 18E, NtAI score. Numbersrepresents the same cell lines as in FIG. 10 (1).

FIG. 19 shows receiver operating characteristic curve showing theability of NtAI to predict for sensitivity to platinum-based therapy inwtBRCA serous ovarian cancer.

FIG. 20 shows distribution of dsDNA breaks resulting in telomericallelic imbalance and association with common CNVs according tocisplatin response. Squares indicate inferred chromosomal location ofdsDNA breaks resulting in tAI, pooled from both trials. Stacked squaresrepresent multiple tumors with dsDNA breaks at the same position.

FIGS. 21A-21B show BRCA1 expression and NtAI versus response tocisplatin in Cisplatin-1 and Cisplatin-2 combined. FIG. 21A showsidentification of the optimum cut-off for NtAI (black) and BRCA1 mRNA(blue) to predict cisplatin response separately. Filled circlesrepresent optimum cut-points. FIG. 21B shows how the combination ofBRCA1 expression and NtAI may improve prediction of cisplatin response.Red indicates samples sensitive to cisplatin. Lines represents theoptimum cut-off for prediction of response based on NtAI and BRCA1 mRNA,as determined in FIG. 21A. “Sens” represents the number of sensitive pertotal cases shown in each quadrant defined by the NtAI and BRCA1 mRNAcut-offs. The table shows the prediction accuracy based on the definedcut-offs for NtAI alone, BRCA1 mRNA alone, and the two measurementscombined. ACC: accuracy. PPV: positive predictive value. NPV: negativepredictive value. SENS: sensitivity. SPEC: specificity. P: p-value basedon Fishers exact test. This table is based only on the samples shown inFIG. 21B.

FIGS. 22A-22C show BRCA1 expression by gene expression micro array inTCGA cohorts. FIG. 22A. BRCA1 mRNA expression versus NtAI in the TCGAER−/HER2− breast cancers (n=78). FIG. 22B shows BRCA1 mRNA expressionversus NtAI in the TCGA wtBRCA serous ovarian cancers (n=165). FIG. 22Cshows BRCA1 mRNA expression versus treatment response in the TCGA wtBRCAserous ovarian cancers.

FIG. 23 shows an exemplary process by which a computing system candetermine a chromosomal aberration score

FIG. 24 is a diagram of an example of a computer device 1400 and amobile computer device 1450, which may be used with the techniquesdescribed herein.

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to methods for predicting response of acancer in a subject to anti-cancer therapies based upon a determinationand analysis of a chromosomal aberration score, such as the number ofallelic imbalance or the number of telomeric allelic imbalance in thechromosomes of the human genome.

According to one aspect of the invention, Global Chromosomal AberrationScore (GCAS) is a measurement predictive of responsiveness toanti-cancer therapies of a cancer in a subject. This utility of GCAS isbased upon the novel finding that the summation of individualchromosomal aberrations can predict responsiveness of a cancer in asubject to anti-cancer agents independently of identifying specificchromosomal aberrations. Informative loci of interest (e.g., singlenucleotide polymorphisms (SNPs), restriction fragment lengthpolymorphisms (RFLPs), simple tandem repeats (STRs), etc.), are used todetermine GCAS as they are useful for detecting and/or distinguishingchromosomal aberrations. As used herein, “chromosomal aberration” meansallelic imbalance (AI), loss of heterozygosity (LOH), copy numberaberrations (CNA), copy number gain (CNG), copy number decrease (CND)and combinations thereof. GCAS is a type of chromosomal aberrationscore, of which other types include telomeric aberration score,telomeric allelic imbalance score, etc. Thus, unless explicitly statedotherwise or unless the context clearly indicates otherwise, referencesto GCAS may apply in some embodiments equally to other chromosomalaberration scores (e.g., telomeric aberration score, telomeric allelicimbalance score, etc.).

GCAS is determined by determining a plurality or the total number ofchromosome regions displaying allelic imbalance (NAI), loss ofheterozygosity (LOH), copy number aberrations (NCNA), copy number gain(NCNG), and/or copy number decrease (NCND), as described further hereinand according to methods well-known in the art. A GCAS of at least 2, 3,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58,59, or 60 or more is predictive of response to anti-cancer therapy ofthe cancer cell from which the assayed nucleic acid was derived.

In one embodiment, the analysis is based upon nucleic acids obtainedfrom a subject and/or control sample. Such samples can include “bodyfluids,” which refer to fluids that are excreted or secreted from thebody as well as fluids that are normally not (e.g. amniotic fluid,aqueous humor, bile, blood and blood plasma, cerebrospinal fluid,cerumen and earwax, cowper's fluid or pre-ejaculatory fluid, chyle,chyme, stool, female ejaculate, interstitial fluid, intracellular fluid,lymph, menses, breast milk, mucus, pleural fluid, pus, saliva, sebum,semen, serum, sweat, synovial fluid, tears, urine, vaginal lubrication,vitreous humor, vomit). In a preferred embodiment, the subject and/orcontrol sample is selected from the group consisting of cells, celllines, histological slides, paraffin embedded tissues, biopsies, wholeblood, nipple aspirate, serum, plasma, buccal scrape, saliva,cerebrospinal fluid, urine, stool, and bone marrow.

In one embodiment, SNPs are used in determining GCAS, for predictingresponsiveness of a cancer to an anti-cancer therapy. There are sixpossible SNP types, either transitions (A< >T or G< >C) or transversions(A< >G, A< >C, G< >T or C< >T). SNPs are advantageous in that largenumbers can be identified.

In some embodiments, the SNPs or other genomic loci can be scored todetect copy number abnormalities. In such cases, such genomic loci donot need to be informative in terms of genotype since copy number isdetermined by hybridization intensities and doesn't depend on thegenotype. Also, copy number abnormalities can be detected using methodsthat do not use SNPs, such as, for example, array CGH using BAC, cDNAand/or oligonucleotide arrays; microsatellite markers; STRs, RFLPS; etc.

For example, methods for evaluating copy number of nucleic acid in asample include, but are not limited to, hybridization-based assays. Onemethod for evaluating the copy number of encoding nucleic acid in asample involves a Southern Blot. In a Southern Blot, the genomic DNA(typically fragmented and separated on an electrophoretic gel) ishybridized to a probe specific for the target region. Comparison of theintensity of the hybridization signal from the probe for the targetregion with control probe signal from analysis of normal genomic DNA(e.g., a non-amplified portion of the same or related cell, tissue,organ, etc.) provides an estimate of the relative copy number of thetarget nucleic acid. Alternatively, a Northern blot may be utilized forevaluating the copy number of encoding nucleic acid in a sample. In aNorthern blot, mRNA is hybridized to a probe specific for the targetregion. Comparison of the intensity of the hybridization signal from theprobe for the target region with control probe signal from analysis ofnormal mRNA (e.g., a non-amplified portion of the same or related cell,tissue, organ, etc.) provides an estimate of the relative copy number ofthe target nucleic acid. Similar methods for determining copy number canbe performed using transcriptional arrays, which are well-known in theart.

An alternative means for determining the copy number is in situhybridization (e.g., Angerer (1987) Meth. Enzymol 152: 649). Generally,in situ hybridization comprises the following steps: (1) fixation oftissue or biological structure to be analyzed; (2) prehybridizationtreatment of the biological structure to increase accessibility oftarget DNA, and to reduce nonspecific binding; (3) hybridization of themixture of nucleic acids to the nucleic acid in the biological structureor tissue; (4) post-hybridization washes to remove nucleic acidfragments not bound in the hybridization and (5) detection of thehybridized nucleic acid fragments. The reagent used in each of thesesteps and the conditions for use vary depending on the particularapplication.

Preferred hybridization-based assays include, but are not limited to,traditional “direct probe” methods such as Southern blots or in situhybridization (e.g., FISH and FISH plus SKY), and “comparative probe”methods such as comparative genomic hybridization (CGH), e.g.,cDNA-based or oligonucleotide-based CGH. The methods can be used in awide variety of formats including, but not limited to, substrate (e.g.membrane or glass) bound methods or array-based approaches.

In a typical in situ hybridization assay, cells are fixed to a solidsupport, typically a glass slide. If a nucleic acid is to be probed, thecells are typically denatured with heat or alkali. The cells are thencontacted with a hybridization solution at a moderate temperature topermit annealing of labeled probes specific to the nucleic acid sequenceencoding the protein. The targets (e.g., cells) are then typicallywashed at a predetermined stringency or at an increasing stringencyuntil an appropriate signal to noise ratio is obtained.

The probes are typically labeled, e.g., with radioisotopes orfluorescent reporters. Preferred probes are sufficiently long so as tospecifically hybridize with the target nucleic acid(s) under stringentconditions. The preferred size range is from about 200 bases to about1000 bases.

In some applications it is necessary to block the hybridization capacityof repetitive sequences. Thus, in some embodiments, tRNA, human genomicDNA, or Cot-I DNA is used to block non-specific hybridization.

In CGH methods, a first collection of nucleic acids (e.g., from asample, e.g., a possible tumor) is labeled with a first label, while asecond collection of nucleic acids (e.g., a control, e.g., from ahealthy cell/tissue) is labeled with a second label. The ratio ofhybridization of the nucleic acids is determined by the ratio of the two(first and second) labels binding to each fiber in the array. Wherethere are chromosomal deletions or multiplications, differences in theratio of the signals from the two labels will be detected and the ratiowill provide a measure of the copy number. Array-based CGH may also beperformed with single-color labeling (as opposed to labeling the controland the possible tumor sample with two different dyes and mixing themprior to hybridization, which will yield a ratio due to competitivehybridization of probes on the arrays). In single color CGH, the controlis labeled and hybridized to one array and absolute signals are read,and the possible tumor sample is labeled and hybridized to a secondarray (with identical content) and absolute signals are read. Copynumber difference is calculated based on absolute signals from the twoarrays. Hybridization protocols suitable for use with the methods of theinvention are described, e.g., in Albertson (1984) EMBO J. 3: 1227-1234;Pinkel (1988) Proc. Natl. Acad. Sci. USA 85: 9138-9142; EPO Pub. No.430,402; Methods in Molecular Biology, Vol. 33: In situ HybridizationProtocols, Choo, ed., Humana Press, Totowa, N.J. (1994), etc. In oneembodiment, the hybridization protocol of Pinkel, et al. (1998) NatureGenetics 20: 207-211, or of Kallioniemi (1992) Proc. Natl Acad Sci USA89:5321-5325 (1992) is used.

The methods of the invention are particularly well suited to array-basedhybridization formats. Array-based CGH is described in U.S. Pat. No.6,455,258, the contents of which are incorporated herein by reference.In still another embodiment, amplification-based assays can be used tomeasure copy number. In such amplification-based assays, the nucleicacid sequences act as a template in an amplification reaction (e.g.,Polymerase Chain Reaction (PCR). In a quantitative amplification, theamount of amplification product will be proportional to the amount oftemplate in the original sample. Comparison to appropriate controls,e.g. healthy tissue, provides a measure of the copy number.

Methods of “quantitative” amplification are well known to those of skillin the art. For example, quantitative PCR involves simultaneouslyco-amplifying a known quantity of a control sequence using the sameprimers. This provides an internal standard that may be used tocalibrate the PCR reaction. Detailed protocols for quantitative PCR areprovided in Innis, et al. (1990) PCR Protocols, A Guide to Methods andApplications, Academic Press, Inc. N.Y.). Measurement of DNA copy numberat microsatellite loci using quantitative PCR anlaysis is described inGinzonger, et al. (2000) Cancer Research 60:5405-5409. The known nucleicacid sequence for the genes is sufficient to enable one of skill in theart to routinely select primers to amplify any portion of the gene.Fluorogenic quantitative PCR may also be used in the methods of theinvention. In fluorogenic quantitative PCR, quantitation is based onamount of fluorescence signals, e.g., TaqMan and sybr green.

Other suitable amplification methods include, but are not limited to,ligase chain reaction (LCR) (see Wu and Wallace (1989) Genomics 4: 560,Landegren, et al. (1988) Science 241:1077, and Barringer et al. (1990)Gene 89: 117), transcription amplification (Kwoh, et al. (1989) Proc.Natl. Acad. Sci. USA 86: 1173), self-sustained sequence replication(Guatelli, et al. (1990) Proc. Nat. Acad. Sci. USA 87: 1874), dot PCR,and linker adapter PCR, etc.

In still other embodiments of the methods provided herein, sequencing ofindividual nucleic molecules (or their amplification products) isperformed, as an alternative to hybridization-based assays, usingnucleic acid sequencing techniques. In one embodiment, a high throughputparallel sequencing technique that isolates single nucleic acidmolecules of a population of nucleic acid molecules prior to sequencingmay be used. Such strategies may use so-called “next generationsequencing systems” including, without limitation, sequencing machinesand/or strategies well known in the art, such as those developed byIllumina/Solexa (the Genome Analyzer; Bennett et al. (2005)Pharmacogenomics, 6:373-20 382), by Applied Biosystems, Inc. (the SOLiDSequencer; solid.appliedbiosystems.com), by Roche (e.g., the 454 GS FLXsequencer; Margulies et al. (2005) Nature, 437:376-380; U.S. Pat. Nos.6,274,320; 6,258,568; 6,210,891), by HELISCOPE™ system from HelicosBiosciences (see, e.g., U.S. Patent App. Pub. No. 2007/0070349), and byothers. Other sequencing strategies such as stochastic sequencing (e.g.,as developed by Oxford Nanopore) may also be used, e.g., as described inInternational Application No. PCT/GB2009/001690 (pub. no.WO/2010/004273). All of the copy number determining strategies describedherein can similarly be applied to any of other nucleic acid-basedanalysis described herein, such as for informative loci and the likedescribed further below.

In other embodiments, SNPs can be scored for heterozygosity or absenceof heterozygosity. Techniques like major copy proportion analysisutilize the allelic-imbalance and copy number information to extend theanalyses that can be performed with copy number of LOH events alonesince they can involve copy number deletion, neutral, or gain events. Inother embodiments, to determine the GCAS of a cancer in a subject,heterozygous SNPs located throughout the genome are identified usingnucleic acid samples derived from non-cancerous tissue of the subject ora population of subjects of a single species, and the number isdetermined of those heterozygous SNPs identified that maintainheterozygosity (or alternatively do not exhibit heterozygosity, i.e.,have lost heterozygosity) in a nucleic acid sample of, or derived from,genomic DNA of cancerous tissue of the subject. A nucleic acid sample“derived from” genomic DNA includes but is not limited to pre-messengerRNA (containing introns), amplification products of genomic DNA orpre-messenger RNA, fragments of genomic DNA optionally with adapteroligonucleotides ligated thereto or present in cloning or other vectors,etc. (introns and noncoding regions should not be selectively removed).

All of the SNPs known to exhibit heterozygosity in the species to whichthe subject with cancer belongs need not be included in the number ofheterozygous SNPs used or analyzed. In some embodiments, at least 45,50, 75, 100, 125, 150, 175, 200, 225, 250, 275, 300, 350, 400, 450, 500,550, 600, 650, 700, 750, 800, 850, 900, 950, 1,000, 2,000, 3,000, 4,000,5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 11,000, 12,000, 13,000,14,000, 15,000, 16,000, 17,000, 18,000, 19,000, 20,000, 21,000, 22,000,23,000, 24,000, 25,000, 26,000, 27,000, 28,000, 29,000, 30,000, 31,000,32,000, 33,000,34,000, 35,000, 36,000, 37,000, 38,000, 39,000, 40,000,41,000, 42,000, 43,000, 44,000, 45,000, 50,000, 60,000, 70,000, 80,000,90,000, 100,000, 150,000, 200,000, 250,000, 300,000, 350,000, 400,000,450,000, 500,000, 550,000, 600,000, 650,000, 700,000, 750,000, 800,000,850,000, 900,000, 950,000, 1,000,000 SNPs or more, or any range inbetween, or other informative loci of interest (e.g., RFLPs, STRs, etc.)are used. Preferably, such SNPs are in the human genome. In oneembodiment, the plurality of heterozygous SNPs are randomly distributedthroughout the genome at least every 1, 5, 10, 50, 100, 250, 500, 1,000,1,500, 2,000, 2,500, 3,000, 5,000, 10,000 kb or more, or any range inbetween. By “randomly distributed,” as used above, is meant that theSNPs of the plurality are not selected by bias toward any specificchromosomal locus or loci; however, other biases (e.g., the avoidance ofrepetitive DNA sequences) can be used in the selection of the SNPs. Inother embodiments, the plurality of heterozygous SNPs are not randomlydistributed throughout the genome (i.e., distributed within at least250, 500, 1,000, 1,500, 2,000, 2,500, 3,000, 5,000, 10,000, 11,000,12,000, 13,000, 14,000, 15,000, 16,000, 17,000, 18,000, 19,000, 20,000,21,000, 22,000, 23,000, 24,000, or 25,000 kb=25 Mb). Such regions canfurther be biased, in some embodiments, to specific chromosomal regionssuch as telomeres (sometimes herein called “telomeric regions” or“telomeric segments”) defined as regions extending toward the telomerebut not crossing the centromere. In one embodiment, the telomericallelic imbalance segment size is at least 1 Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb,6 Mb, 7 Mb, 8 Mb, 9 Mb, 10 Mb, 11 Mb, 12 Mb, 13 Mb, 14 Mb, 15 Mb, 16 Mb,17 Mb, 18 Mb, 19 Mb, 20 Mb, 21 Mb, 22 Mb, 23 Mb, 24 Mb, 25 Mb, or more,or any range in between, such as between 5 and 25 Mb. In anotherembodiment, the telomeric allelic imbalance segment size is 12 Mb. Bycontrast, interstitial regions do not involve the telomere. Interstitialregions are defined herein as regions of allelic imbalance that startdownstream of the telomere meaning that there is at least some part ofthe chromosome with no allelic imbalance between the telomere and theregion of allelic imbalance. In one embodiment, the plurality ofheterozygous SNPs is not found in regions of genomic DNA that arerepetitive. In another embodiment, the plurality of heterozygous SNPscomprises SNPs located in the genome on different chromosomal loci,wherein the different chromosomal loci comprise loci on each of thechromosomes of the species, or on each arm of each chromosome of thespecies (e.g., telomeric region thereof).

With many modern high-throughput techniques (including those discussedherein), it is possible to determine genotype, copy number, copyproportion, etc. for tens, hundreds, thousands, millions or evenbillions of genomic loci (e.g., all known heterozygous SNPs in aparticular species, whole genome sequencing, etc.). Once a global assayhas been performed (e.g., assaying all or substantially all knownheterozygous SNPs), one may then informatically analyze one or moresubsets of loci (i.e., panels of test loci or, as sometimes used herein,pluralities of test loci). Thus, in some embodiments, after assaying forallelic imbalance in hundreds of loci or more in a sample (or afterreceiving the data from such an assay), one may analyze (e.g.,informatically) a panel or plurality of test loci according to thepresent invention (e.g., entirely or primarily telomeric SNPs) bycombining the data relating to the individual test loci to obtain a testvalue indicative of the overall level, nature, etc. of allelic imbalancein the desired group of test loci.

Thus, in one aspect the invention provides a method of deriving achromosomal aberration score (e.g., GCAS, telomeric aberration score,telomeric allelic imbalance score, etc.) comprising: determining whethera sample has a chromosomal aberration (e.g., of allelic imbalance, lossof heterozygosity, copy number aberrations, copy number gain, copynumber decrease) at a plurality of assay (e.g., genomic) loci; analyzinga plurality of test loci within said plurality of assay loci forchromosomal aberrations; combining the data from (2) to derive a scorereflecting the overall extent of chromosomal aberration in saidplurality of test loci, thereby deriving a chromosomal aberration score.

In some embodiments determining whether a sample has a chromosomalaberration at the plurality of assay loci comprises assaying a tissuesample (e.g., physically processing a tangible patient specimen toderive data therefrom) and analyzing the data (e.g., SNP genotype data)derived from such assay. In some embodiments, determining whether asample has a chromosomal aberration at the plurality of assay locicomprises analyzing data derived from an assay on a tissue sample.

In some embodiments the assay loci represent all loci analyzed in therelevant assay (e.g., all heterozygous SNPs represented on theparticular SNP array, all nucleotides in a sequencing assay). In someembodiments the assay loci represent particular loci analyzed in therelevant assay (e.g., certain nucleotides, such as SNPs, in a sequencingassay). In some embodiments all assay loci are test loci. In someembodiments the test loci represent at least some percentage (e.g., 5%,10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or 100%) of theassay loci. In some embodiments at least some percentage (e.g., 5%, 10%,15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or 100%) of the assayloci are telomeric loci. In some embodiments at least some percentage(e.g., 5%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or100%) of the test loci are telomeric loci. Thus, in some embodiments theinvention provides a method of deriving a chromosomal aberration score(e.g., GCAS, telomeric aberration score, telomeric allelic imbalancescore, etc.) comprising: determining whether a sample has a chromosomalaberration (e.g., of allelic imbalance, loss of heterozygosity, copynumber aberrations, copy number gain, copy number decrease) at aplurality of assay (e.g., genomic) loci; analyzing a plurality of testloci within said plurality of assay loci for chromosomal aberrations,wherein at least 5% (or 10%, or 15%, or 20%, or 30%, or 40%, or 50%, or60%, or 70%, or 80%, or 90%, or 95%, or 100%) of the test loci aretelomeric loci; combining the data from (2) to derive a score reflectingthe overall extent of chromosomal aberration in said plurality of testloci, thereby deriving a chromosomal aberration score.

In some embodiments each test locus is assigned a particular weight incalculating the chromosomal aberration score. In some embodiments testloci are assigned a weight by each being given a particular coefficientin a formula (final or intermediate) used to calculate the chromosomalaberration score. In some embodiments telomeric test loci (all or atleast 5%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% oftelomeric test loci) are weighted such that they contribute at leastsome percentage (5%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%,95% or 100%) to the chromosomal aberration score. Thus, in someembodiments the invention provides a method of deriving a chromosomalaberration score (e.g., GCAS, telomeric aberration score, telomericallelic imbalance score, etc.) comprising: determining whether a samplehas a chromosomal aberration (e.g., of allelic imbalance, loss ofheterozygosity, copy number aberrations, copy number gain, copy numberdecrease) at a plurality of assay (e.g., genomic) loci; analyzing aplurality of test loci within said plurality of assay loci forchromosomal aberrations; combining the data from (2) to derive a scorereflecting the overall extent of chromosomal aberration in saidplurality of test loci, wherein each test locus is assigned a weightingcoefficient that determines its contribution to the chromosomalaberration score and wherein telomeric loci are weighted such that theycontribute at least 5% (or 10%, or 15%, or 20%, or 30%, or 40%, or 50%,or 60%, or 70%, or 80%, or 90%, or 95%, or 100%) to the chromosomalaberration score, thereby deriving a chromosomal aberration score.

“Telomeric locus” as used herein means a locus within a telomere orwithin some defined distance along the chromosome from the telomere. Insome embodiments a telomeric locus is within 1 Kb, 2 Kb, 3 Kb, 4 Kb, 5Kb, 6 Kb, 7 Kb, 8 Kb, 9 Kb, 10 Kb, 15 Kb, 20 Kb, 25 Kb, 30 Kb, 35 Kb, 40Kb, 45 Kb, 50 Kb, 100 Kb, 200 Kb, 300 Kb, 400 Kb, 500 Kb, 750 Kb, 1 Mb,2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, 10 Mb, 15 Mb, 20 Mb, 25Mb, 30 Mb, 35 Mb, 40 Mb, 45 Mb, 50 Mb, 60 Mb, 70 Mb, 80 Mb, 90 Mb, or100 Mb or less of the telomere. In some embodiments, the distancebetween the telomeric locus and the telomere is less than 1%, 2%, 3%,4%, 5%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% of thelength of the entire chromosome arm.

Thus, in some embodiments a telomeric region or telomeric segment is achromosomal region encompassing at least some number of telomeric loci(e.g., at least 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, 75, 100, 150, 200,250, 300, 400, 500, 750, 1,000, 1,500, 2,000, 2,500, 3,000, 4,000,5,000, 7,500, or 10,000 or more telomeric loci). In some embodiments atelomeric region or telomeric segment is a chromosomal regionencompassing at least 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, 75, 100, 150,200, 250, 300, 400, 500, 750, 1,000, 1,500, 2,000, 2,500, 3,000, 4,000,5,000, 7,500, or 10,000 or more telomeric loci, wherein such telomericloci are within 50 Kb, 100 Kb, 200 Kb, 300 Kb, 400 Kb, 500 Kb, 750 Kb, 1Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, or 10 Mb of thetelomere (or any such combination of number of telomeric loci anddistance of such loci from the telomere). In some embodiments telomericregions do not cross the centromere.

DNA repair competency is one determinant of sensitivity to certainchemotherapy drugs, such as cisplatin. Cancer cells with intact DNArepair can avoid the accumulation of genome damage during growth andalso can repair platinum-induced DNA damage. We sought genomicsignatures indicative of defective DNA repair in cell lines and tumors,and correlated these signatures to platinum sensitivity. The number ofsub-chromosomal regions with allelic imbalance extending to the telomere(NtAI) predicted cisplatin sensitivity in-vitro, and pathologic responseto preoperative cisplatin treatment in patients with triple-negativebreast cancer (TNBC). In serous ovarian cancer treated withplatinum-based chemotherapy, higher NtAI forecast better initialresponse. We found an inverse relationship between BRCA1 expression andnumber of regions of tAI (NtAI) in sporadic TNBC and serous ovariancancers without BRCA1 or BRCA2 mutation. Thus, accumulation of tAI is amarker of cisplatin sensitivity and suggests impaired DNA repair, andNtAI can be useful for predicting response to treatments targetingdefective DNA repair.

Mutations in BRCA1 or BRCA2 cause defects in DNA repair that predictsensitivity to platinum salts in breast and ovarian cancer; however,some patients without BRCA mutations also benefit from these agents.This study shows that defects in DNA repair that cause platinumsensitivity can be inferred from the number of allelic imbalance (NAI),for example, the number of telomeric imbalance (NtAI), a measure ofgenomic aberration in tumors. We have demonstrated that NAI and/or NtAIcan identify cancer patients without BRCA mutations who are likely tobenefit from platinum-based therapy, such as cancer patients with triplenegative breast cancer or triple negative ovarian cancer.

Cell lines carrying BRCA1 or BRCA2 mutations are more sensitive tokilling by the platinum salts cisplatin and carboplatin than wild-typecells (Samouelian, et al. Chemosensitivity and radiosensitivity profilesof four new human epithelial ovarian cancer cell lines exhibitinggenetic alterations in BRCA2, TGFbeta-RII, KRAS2, TP53 and/or CDNK2A.Cancer Chemother Pharmacol 2004; 54: 497-504, Tassone, et al. BRCA1expression modulates chemosensitivity of BRCA1-defective HCC1937 humanbreast cancer cells. Br J Cancer 2003; 88: 1285-1291). Breast andovarian cancers in patients carrying BRCA1 or BRCA2 mutations arelikewise sensitive to platinum-based chemotherapy (Byrski, T., et al.Response to neoadjuvant therapy with cisplatin in BRCA1-positive breastcancer patients. Breast Cancer Res Treat 2009; 115: 359-363, Cass, I.,et al. Improved survival in women with BRCA-associated ovariancarcinoma. Cancer 2003; 97: 2187-2195). The majority of breast cancersarising in women with a germline BRCA1 mutation lack expression ofestrogen and progesterone receptors or amplification of the HER2-neugene (“triple-negative”). BRCA1-related breast cancers share a number ofphenotypic characteristics with sporadic triple-negative breast cancer(TNBC) (Turner, N. C., et al. BRCA1 dysfunction in sporadic basal-likebreast cancer. Oncogene 2007; 26: 2126-2132; Sorlie, T., et al. Repeatedobservation of breast tumor subtypes in independent gene expression datasets. Proc Natl Acad Sci USA 2003; 100: 8418-8423; Lakhani, S. R., etal. Prediction of BRCA1 status in patients with breast cancer usingestrogen receptor and basal phenotype. Clin Cancer Res 2005; 11:5175-5180). Both tumor types share a common pattern of genomicabnormalities and have high global levels of chromosomal aberrationsincluding allelic imbalance (AI), the unequal contribution of maternaland paternal DNA sequences with or without changes in overall DNA copynumber (Wang, Z. C., et al. Loss of heterozygosity and its correlationwith expression profiles in subclasses of invasive breast cancers.Cancer Research 2004; 64: 64-71; Richardson, A. L., et al. X chromosomalabnormalities in basal-like human breast cancer. Cancer Cell 2006; 9:121-132; Van Loo, P., et al. Allele-specific copy number analysis oftumors. Proc Natl Acad Sci USA 2010; 107: 16910-16915). Since they havein common genomic aberrations suggesting a shared lesion in genomicintegrity control, it is reasonable to posit sporadic TNBC that hasaccumulated high levels of AI might share the sensitivity toplatinum-based chemotherapy that characterizes BRCA1-associated cancer.

We performed a clinical trial, Cisplatin-1, in which 28 patients withoperable TNBC were treated preoperatively with cisplatin monotherapy.Preoperative treatment in Cisplatin-1 resulted in greater than 90% tumorreduction in 10 of 28 (36%) patients, including pathologic completeresponse (pCR) in 6 women, 2 of whom had BRCA1-associated cancers(Silver, D. P., et al. Efficacy of neoadjuvant Cisplatin intriple-negative breast cancer. J Clin Oncol 2010; 28: 1145-1153). Asecond trial, Cisplatin-2, accrued 51 patients with TNBC who receivedthe same preoperative cisplatin regimen as Cisplatin-1, but incombination with the angiogenesis inhibitor bevacizumab (Ryan, P. D., etal. Neoadjuvant cisplatin and bevacizumab in triple negative breastcancer (TNBC): Safety and Efficacy. J Clin Oncol 2009; 27: 551).Response rate in Cisplatin-2 were similar to Cisplatin-1. In the secondtrial, a greater than 90% tumor reduction was observed in 17 of 44 women(39%) completing treatment. In Cisplatin-2, 8 patients carried agermline BRCA1 or BRCA2 mutation, of which 4 patients achieved a pCR ornear pCR to the cisplatin-bevacizumab regimen. In both trials, allpatients had research sequencing to determine their germline BRCA1 andBRCA2 status. Thus in some aspects of all the embodiments of theinvention, the BRCA1 and BRCA2 status can be determined eithersimultaneously with or before the allelic imbalance or telomeric allelicimbalance analysis. In some aspects, only patients without BRCA1 orBRCA2 mutations are subjected to the NAI (number of allelic imbalance)or NtAI (number of telomeric allelic imbalance) assays or analyses.Cisplatin was used as an example of platinum comprising cancertherapies.

We compared the number of various chromosomal abnormalities including AIpresent in tumor biopsies obtained before therapy to pathologicallydetermined tumor response to cisplatin, alone or in combination withbevacizumab, assessed by examination of the post-treatment surgicalspecimen.

Without wishing to be bound by theory, chromosomal abnormalities such asregions of allelic imbalance, other than those resulting from wholechromosome gain or loss, can result from improper repair of DNAdouble-strand breaks during tumor development. If so, then a genome-widecount of abnormal chromosomal regions in tumors can indicate the degreeof DNA repair incompetence, independent of knowledge of any specificcausative DNA repair defect. We hypothesized that the number ofchromosomal regions of AI in tumors would predict sensitivity to drugsthat induce DNA crosslinks such as cisplatin.

We sought associations between various measures of sub-chromosomalabnormalities and sensitivity to cisplatin in breast cancer cell linesand found the most accurate predictor to be AI extending to thetelomeric end of the chromosome (NtAI). Finally, we tested if NtAI wasassociated with treatment response in patient tumor samples in theCisplatin-1 and Cisplatin-2 TNBC trials and in The Cancer Genome Atlas(TCGA) public data set of serous ovarian cancer, a cancer routinelytreated with platinum-based therapy. In an effort to understand moreabout the processes leading to telomeric allelic imbalances, we mappedthe location of their breakpoints and observed a striking association ofthese breakpoints with regions of the genome that are difficult toreplicate, common copy number variants (CNVs). Further, a subset of highNtAI tumors display low BRCA1 mRNA levels. These observations begin tosuggest models of how tAI may occur.

We showed that Cisplatin sensitivity correlates with burden, i.e.increase in the number of telomeric allelic imbalance compared to normalcells in, for example, breast cancer cell lines. We obtained singlenucleotide polymorphism (SNP) genotype array data from the WellcomeTrust Sanger Institute for a set of established BRCA1 wild-type breastcancer cell lines for which we had determined cisplatin sensitivity (Li,Y., et al. Amplification of LAPTM4B and YWHAZ contributes tochemotherapy resistance and recurrence of breast cancer. Nat Med 2010;16: 214-218) (FIG. 10A). Allele copy number was determined from the SNParray data and AI detected using ASCAT analysis (10) (FIG. 16), althoughany other allelic imbalance analysis can be used as well. We tested forassociation between the IC₅₀ values for cisplatin and each of threesummary measures of chromosomal alteration: the number of chromosomeregions with AI (NAI, FIG. 17A), the number of regions with copy numbergains (NGain, FIG. 17B), and the number of regions with copy number loss(NLoss, FIG. 17C). None of these measures were correlated with cisplatinsensitivity in the cell lines.

Known defects in DNA double strand break repair, including loss ofBRCA1, cause the spontaneous formation of triradial and quadriradialchromosome structures, which are cytologic indications of aberrantchromosome recombination (Silver, D. P., et al. Further evidence forBRCA1 communication with the inactive X chromosome. Cell 2007; 128:991-1002; Luo, G., et al. Cancer predisposition caused by elevatedmitotic recombination in Bloom mice. Nat Genet 2000; 26: 424-429; Xu,X., et al., Centrosome amplification and a defective G2-M cell cyclecheckpoint induce genetic instability in BRCA1 exon 11 isoform-deficientcells. Mol Cell 1999; 3: 389-395). The resolution of these chromosomerearrangements at mitosis can result in large regions of AI and/or copynumber changes extending from the crossover to the telomere (Luo, G., etal. Cancer predisposition caused by elevated mitotic recombination inBloom mice. Nat Genet 2000; 26: 424-429; Vrieling, H. Mitotic maneuversin the light. Nat Genet 2001; 28: 101-102). More generally, severalerror-prone repair processes potentially employed by cells withdefective DNA repair cause chromosome cross-over or copy choice eventsthat result in allelic loss or copy number change extending from thesite of DNA damage to the telomere.

We looked for an association between cisplatin sensitivity and thenumber of contiguous regions of AI, copy gain, or copy loss that eitherextended to a telomere and did not cross the centromere (telomericregions) or did not extend to a telomere (interstitial regions) (FIG.16, FIG. 10B, and FIG. 18). The number of regions of telomeric AI (NtAI)was the only summary genomic measure that was significantly associatedwith cisplatin sensitivity in the breast cancer cell lines (r=0.76P=0.011, FIG. 10B); the correlation between NtAI and cisplatinsensitivity was stronger when the analysis was restricted to the triplenegative breast cancer lines (FIG. 1B, red circles; r=0.82 P=0.0499). Asimilar relationship was observed between NtAI and cisplatin sensitivityas measured by G150 in a recently published study of breast cancer celllines (r=0.57 P=0.0018, FIG. 10C) (18). Of all the drugs tested in thisstudy, NtAI was most highly correlated to cisplatin sensitivity.

We showed that tumors sensitive to cisplatin-based chemotherapy havehigher levels of telomeric allelic imbalance. We investigated whetherthe association between NtAI in clinical tumor samples and cisplatinsensitivity was present in the Cisplatin-1 trial. Sensitivity wasmeasured by pathologic response determined after pre-operative treatment(Silver, D. P., et al. Efficacy of neoadjuvant Cisplatin intriple-negative breast cancer. J Clin Oncol 2010; 28: 1145-1153).Molecular inversion probe SNP genotype data from pretreatment tumorsamples (n=27) were evaluated by ASCAT analysis to determine NtAI. Wecompared tumors with a reduction of at least 90% in the content ofmalignant cells (cisplatin sensitive) to tumors with limited or noresponse to cisplatin (cisplatin resistant, defined by tumor reductionof less than 90%).

We showed that cisplatin sensitive tumors had significantly higher NtAI(median 24 versus 17.5, P=0.047, FIG. 11A). We tested the ability ofNtAI to predict cisplatin response by calculating the area under thereceiver operating characteristic (ROC) curve (AUC). ROC analysis showedthat higher NtAI was associated with cisplatin sensitivity (AUC=0.74, CI0.50-0.90, FIG. 11B).

In the Cisplatin-2 trial, cisplatin sensitive tumors (n=9) hadsignificantly higher NtAI than resistant tumors (n=17, median 27 versus20, P=0.019, FIG. 11C). NtAI was also associated with response tocisplatin and bevacizumab by ROC analysis (AUC=0.79, CI 0.55-0.93, FIG.11D). The association between NtAI and cisplatin sensitivity remainedsignificant when cases with BRCA1 or BRCA2 mutation were excluded andonly BRCA normal cases were analyzed (P=0.030 and P=0.023 in Cisplatin-1and Cisplatin-2, respectively). Therefore, in two separate pre-operativetrials in breast cancer, in which treatment sensitivity was assessed bya quantitative measure of pathologic response, NtAI reliably forecastthe response to cisplatin-based treatment.

To test if the NtAI metric indicates platinum sensitivity in cancersother than breast, we determined the association between NtAI andinitial treatment response in The Cancer Genome Atlas (TCGA) cohort ofserous ovarian cancer patients that had received adjuvant platinum andtaxane chemotherapy (Bell, D., et al., Integrated genomic analyses ofovarian carcinoma. Nature 2011; 474: 609-615). Again, among the ovariancancers without mutation in BRCA1 or BRCA2 (wtBRCA), the platinumsensitive tumors had significantly higher NtAI than platinum-resistantcancers (median 22 versus 20, P=0.036, FIG. 12), and were predictive oftreatment response by ROC analysis (AUC=0.63, CI 0.50-0.76, FIG. 19).The ovarian cancers with somatic or germline mutation in BRCA1 or BRCA2that were sensitive to platinum therapy had even higher NtAI (median=26,P=0.0017 and median 23.5, P=0.037 versus resistant wtBRCA, respectively,FIG. 12). All of the BRCA2 mutated cancers were platinum sensitive;however, 5 BRCA1 mutated tumors were resistant to platinum therapy yetappeared to have relatively high levels of NtAI. Thus high NtAI ischaracteristic of serous ovarian cancer with known mutation in eitherBRCA1 or BRCA2; high NtAI is also found in a subset of sporadic cancerswithout BRCA mutations where it is predictive of platinum sensitivity.

Accordingly, we provide a method for selecting therapy for a humancancer patient, the method comprising assaying a sample comprising tumorcells taken from the human cancer patient for the number of allelicimbalance, for example telomeric allelic imbalance, and selecting, andoptionally administering a platinum-comprising cancer therapy to thehuman cancer patient if the number of allelic imbalance is increasedcompared to a reference value. The reference value for the number ofallelic imbalance, such as telomeric allelic imbalance can be, forexample, at least 20, at least 21, at least 22, at least 23, at least23.5, at least 24, at least 25, at least 26, at least 27, at least 28 atleast 29, or at least 30. The reference value can be determined for eachtumor, for example from the number of allelic imbalance collected fromsimilar cancers that are platinum-resistant. So, for example, in a lungcancer, samples from lung cancer cells from platinum-resistant cancerscan provide a median number of allelic imbalance for the cancer to beused as a reference value for non-responding samples.

We further showed that locations of NtAI-associated chromosomal breaksare not random. To understand the processes leading to tAI better, wemapped the location of the chromosome breakpoints defining the boundaryof the tAI regions. We observed many breakpoints were located in veryclose proximity to each other (FIG. 20), suggesting a non-randomdistribution of DNA breaks causing telomeric allelic imbalance.

Without wishing to be bound by a theory, recurrent chromosomaltranslocation breakpoints can be associated with regions of repeated DNAsequence that can cause stalled replication forks, an increasedfrequency of DNA breaks, and subsequent rearrangement by non-allelichomologous recombination or other similar mechanisms (Kolomietz, E., etal., The role of Alu repeat clusters as mediators of recurrentchromosomal aberrations in tumors. Genes Chromosomes Cancer 2002; 35:97-112; Hastings, P. J., Ira, G., and Lupski, J. R. Amicrohomology-mediated break-induced replication model for the origin ofhuman copy number variation. PLoS Genet 2009; 5: e1000327).

Copy number variants (CNVs) are highly homologous DNA sequences forwhich germline copy number varies between healthy individuals (Iafrate,A. J., et al. Detection of large-scale variation in the human genome.Nat Genet 2004; 36: 949-951; Sebat, J., et al., Large-scale copy numberpolymorphism in the human genome. Science 2004; 305: 525-528). CNVs havebeen proposed to facilitate the generation of chromosomal alterations,similar to fragile sites (Hastings, P. J., Ira, G., and Lupski, J. R. Amicrohomology-mediated break-induced replication model for the origin ofhuman copy number variation. PLoS Genet 2009; 5: e1000327; Stankiewicz,P., et al. Genome architecture catalyzes nonrecurrent chromosomalrearrangements. Am J Hum Genet 2003; 72: 1101-1116; Hastings, P. J., etal., Mechanisms of change in gene copy number. Nat Rev Genet 2009; 10:551-564). We compared the number of observed breaks within 25 kB of aCNV to the frequency expected by chance alone, based on permuted data.In the Cisplatin-1 cohort, of 517 NtAI breakpoints, 255 (49%) wereassociated with overlapping CNVs. Similarly, in the cisplatin-2 cohort,out of 599 NtAI breakpoints, 340 (57%) were associated with CNVs. Inboth trials, the observed number of NtAI breaks associated with CNVs wassignificantly higher than expected by chance (FIG. 13A-13B). Thus manyof the breakpoints leading to telomeric AI in TNBC occur near CNVssuggesting stalled replication forks, replication stress, or otherCNV-associated mechanisms may be involved in the genesis of telomericAI.

Accordingly, in some aspects of all the embodiments of the invention, weprovide a method or an assay for determining whether a patient isresponsive to platinum-comprising therapy by assaying the number ofallelic imbalance, such as telomeric allelic imbalance, wherein the AIis associated with copy number vatiations (CNVs). If increase of CNVassociates NAI, such as NtAI is detected, then determining that thepatient is responsive to platinum-comprising cancer therapy andoptionally administering the platinum-comprising therapy to the cancerpatient. If no increase in CNV associated NAI, such as NtAI is detected,then determining that the cancer patient is not responsive to platinumcomprising cancer therapy and optionally administering to the cancerpatient a non-platinum comprising cancer therapy.

We demonstrated that low BRCA1 mRNA is associated with high NtAI andsensitivity to cisplatin.

According, in some aspects of all the embodiments of the invention, weprovide an assay or a method for determining responsiveness of a cancerpatient to a platinum-comprising cancer therapy, the assay or methodcomprising, assaying in a cancer-cell comprising sample taken from thecancer patient the number of allelic imbalance and/or the BRCA1 mRNAamount, and if the number of allelic imbalance is increased and/or theBRCA1 mRNA amount is decreased, then selecting, and optionallyadministering to the cancer patient platinum-comprising cancer therapy.If, on the other hand no increase in the number of allelic imbalanceand/or no decrease in BRCA1 mRNA amount is detected, then selecting, andoptionally administering to said cancer patient a non-platinumcomprising cancer therapy.

In our Cisplatin-1 trial, we found an association between low BRCA1transcript levels and better response to cisplatin. In the Cisplatin-2trial, BRCA1 transcript levels measured, for example, by qPCR are alsoassociated with cisplatin response (P=0.015, FIG. 14A). In a combinedanalysis of data from both trials, lower BRCA1 transcript levels areassociated with methylation of the BRCA1 promoter (P=0.027, FIG. 14B),though BRCA1 promoter methylation itself is not significantly associatedwith cisplatin response (P=0.25, Fishers exact test). BRCA1 mRNA levelsare inversely associated with NtAI in the two cisplatin trials (r=−0.50,P=0.0053, FIG. 14C). This finding suggests that dysfunction of aBRCA1-dependent process or other abnormality causing low BRCA1 mRNA maybe responsible for the high level of telomeric allelic imbalance andalso cisplatin sensitivity in many of these TNBCs.

In some aspects of all the embodiments of the invention, the assays andmethods comprise assaying the methylation status of BRCA1, whereinincrease in methylation of BRCA1 promoter region is associated with aresponsiveness to platinum-comprising cancer therapy and no increase inmethylation of BRCA1 promoter region is associated with resistance toplatinum-comprising cancer therapy. If increased methylation of BRCA1promoter region is detected, then selecting, and optionallyadministering, a platinum-comprising therapy for the cancer patient, andif no increase in methylation of BRCA1 promoter region is detected, thenselecting, and optionally administering a non-platinum comprisingtherapy for the cancer patient. In some aspects of this embodiment, thecancer is breast cancer.

ROC analysis of the combined TNBC trials suggests that BRCA1 expressionlevel or NtAI may give a similar predictive accuracy for cisplatinsensitivity (FIG. 21A). When high NtAI and low BRCA1 expression arecombined in a predictive model, the positive predictive value andspecificity of prediction improved considerably but the sensitivity wasdecreased relative to NtAI alone (FIG. 21B), suggesting that low BRCA1expression does not account for all cisplatin sensitive tumors.

In the TNBC trials, we noted a few cisplatin sensitive tumors with highlevels of NtAI but high BRCA1 mRNA, suggesting that alternativemechanisms may drive the generation of tAI in some tumors. Analysis ofTCGA data of ER−/HER2− breast cancer and wtBRCA serous ovarian cancerdemonstrate an inverse correlation between NtAI and BRCA1 expression.Yet in both cohorts there was a considerable subset of tumors with highNtAI and high BRCA1 expression (FIG. 22A, 22B). Unlike NtAI, BRCA1expression was not apparently different between sensitive and resistantwtBRCA serous ovarian cancers (FIG. 22C). These findings suggest a modelwhereby high NtAI may represent a readout of DNA repair deficiencyresulting from either low BRCA1 expression or from other known orunknown mechanisms (FIG. 15).

In some aspects of all the embodiments of the invention, the NtAI or NAIanalysis is performed alone without separately detecting or determiningthe status of BRCA1 and/or BRCA2, such as whether the tumor cell carriesa BRCA1 and/or BRCA2 mutation or whether the BRCA1 or BRCA2 expressionis decreased or not, or whether the BRCA1 and/or BRCA2 promotermethylation is increased or not. In some aspects of all the embodimentsof the invention, the NtAI or NAI analysis is performed in combinationwith detecting or determining the status of BRCA1 and/or BRCA2.

Several embodiments of the invention described herein involve a step ofcorrelating an LOH signature or the number of AI or tAI according to thepresent invention (e.g., the total number of LOH/AI/tAI regions in atleast one pair of human chromosomes of said cancer cell that are longerthan a first length but shorter than the length of the whole chromosomecontaining the LOH/AI/tAI region, wherein said at least one pair ofhuman chromosomes is not a human X/Y sex chromosome pair, wherein saidfirst length is about 1.5 or more megabases) to a particular clinicalfeature (e.g., an increased likelihood of a deficiency in the BRCA1 orBRCA2 gene; an increased likelihood of HDR deficiency; an increasedlikelihood of response to a treatment regimen comprising a DNA damagingagent, an anthracycline, a topoisomerase I inhibitor, radiation, and/ora PARP inhibitor; etc.) if the number is greater than some reference (oroptionally to another feature if the number is less than somereference). Throughout this document, wherever such an embodiment isdescribed, another embodiment of the invention may involve, in additionto or instead of a correlating step, one or both of the following steps:(a) concluding that the patient has the clinical feature based at leastin part on the presence or absence of the LOH signature or increase ornot of the number of AI or tAI; or (b) communicating that the patienthas the clinical feature based at least in part on the presence orabsence of the LOH signature or increase of NAI or NtAI.

By way of illustration, but not limitation, one embodiment described inthis document is a method of predicting a cancer patient's response to acancer treatment regimen comprising a DNA damaging agent, ananthracycline, a topoisomerase I inhibitor, radiation, and/or a PARPinhibitor, said method comprising: (1) determining, in a cancer cellfrom said cancer patient, the number of LOH/AI/tAI regions in at leastone pair of human chromosomes of a cancer cell of said cancer patientthat are longer than a first length but shorter than the length of thewhole chromosome containing the LOH/AI/tAI region, wherein said at leastone pair of human chromosomes is not a human X/Y sex chromosome pair,wherein said first length is about 1.5 or more megabases; and (2)correlating said total number that is greater than a reference numberwith an increased likelihood that said cancer patient will respond tosaid cancer treatment regimen. According to the preceding paragraph,this description of this embodiment is understood to include adescription of two related embodiments, i.e., a method of predicting acancer patient's response to a cancer treatment regimen comprising a DNAdamaging agent, an anthracycline, a topoisomerase I inhibitor,radiation, and/or a PARP inhibitor, said method comprising: (1)determining, in a cancer cell from said cancer patient, the number ofLOH/AI/tAI regions in at least one pair of human chromosomes of a cancercell of said cancer patient that are longer than a first length butshorter than the length of the whole chromosome containing theLOH/AI/tAI region, wherein said at least one pair of human chromosomesis not a human X/Y sex chromosome pair, wherein said first length isabout 1.5 or more megabases; and (2)(a) concluding that said patient hasan increased likelihood that said cancer patient will respond to saidcancer treatment regimen based at least in part on a total number thatis greater than a reference number; or (2)(b) communicating that saidpatient has an increased likelihood that said cancer patient willrespond to said cancer treatment regimen based at least in part on atotal number that is greater than a reference number.

In each embodiment described in this document involving correlating aparticular assay or analysis output (e.g., total number of LOH/AI/tAIregions greater than a reference number, etc.) to some likelihood (e.g.,increased, not increased, decreased, etc.) of some clinical feature(e.g., response to a particular treatment, cancer-specific death, etc.),or additionally or alternatively concluding or communicating suchclinical feature based at least in part on such particular assay oranalysis output, such correlating, concluding or communicating maycomprise assigning a risk or likelihood of the clinical featureoccurring based at least in part on the particular assay or analysisoutput. In some embodiments, such risk is a percentage probability ofthe event or outcome occurring. In some embodiments, the patient isassigned to a risk group (e.g., low risk, intermediate risk, high risk,etc.). In some embodiments “low risk” is any percentage probabilitybelow 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or 50%. In someembodiments “intermediate risk” is any percentage probability above 5%,10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or 50% and below 15%, 20%, 25%,30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75%. In some embodiments“high risk” is any percentage probability above 25%, 30%, 35%, 40%, 45%,50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%.

As used herein, “communicating” a particular piece of information meansto make such information known to another person or transfer suchinformation to a thing (e.g., a computer). In some methods of theinvention, a patient's prognosis or likelihood of response to aparticular treatment is communicated. In some embodiments, theinformation used to arrive at such a prognosis or response prediction(e.g., LOH signature or NTAI or NtAI according to the present invention,etc.) is communicated. This communication may be auditory (e.g.,verbal), visual (e.g., written), electronic (e.g., data transferred fromone computer system to another), etc. In some embodiments, communicatinga cancer classification (e.g., prognosis, likelihood of response,appropriate treatment, etc.) comprises generating a report thatcommunicates the cancer classification. In some embodiments the reportis a paper report, an auditory report, or an electronic record. In someembodiments the report is displayed and/or stored on a computing device(e.g., handheld device, desktop computer, smart device, website, etc.).In some embodiments the cancer classification is communicated to aphysician (e.g., a report communicating the classification is providedto the physician). In some embodiments the cancer classification iscommunicated to a patient (e.g., a report communicating theclassification is provided to the patient). Communicating a cancerclassification can also be accomplished by transferring information(e.g., data) embodying the classification to a server computer andallowing an intermediary or end-user to access such information (e.g.,by viewing the information as displayed from the server, by downloadingthe information in the form of one or more files transferred from theserver to the intermediary or end-user's device, etc.).

Wherever an embodiment of the invention comprises concluding some fact(e.g., a patient's prognosis or a patient's likelihood of response to aparticular treatment regimen), this may include in some embodiments acomputer program concluding such fact, typically after performing analgorithm that applies information on LOH/AI/tAI regions according tothe present invention.

In each embodiment described herein involving a number of LOH regions(e.g., LOH Indicator Regions) or a total combined length of such LOHregions, the present invention encompasses a related embodimentinvolving a test value or score (e.g., HRD score, LOH score, NAI, NtAIetc.) derived from, incorporating, and/or, at least to some degree,reflecting such number or length. In other words, the bare LOH/AI/tAIregion numbers or lengths need not be used in the various methods,systems, etc. of the invention; a test value or score derived from suchnumbers or lengths may be used. For example, one embodiment of theinvention provides a method of treating cancer in a patient, comprising:(1) determining in a sample from said patient the number of LOH/AI/tAIregions in at least one pair of human chromosomes of a cancer cell ofthe cancer patient that are longer than a first length but shorter thanthe length of the whole chromosome containing the LOH/AI/tAI regionindicates that the cancer cells have the LOH signature or the number ofAI or tAI, wherein the at least one pair of human chromosomes is not ahuman X/Y sex chromosome pair, wherein the first length is about 1.5 ormore megabases; (2) providing a test value derived from the number ofsaid LOH/AI/tAI regions; (3) comparing said test value to one or morereference values derived from the number of said LOH/AI/tAI regions in areference population (e.g., mean, median, terciles, quartiles,quintiles, etc.); and (4)(a) administering to said patient ananti-cancer drug, or recommending or prescribing or initiating atreatment regimen comprising chemotherapy and/or a synthetic lethalityagent based at least in part on said comparing step revealing that thetest value is greater (e.g., at least 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or10-fold greater; at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standarddeviations greater) than at least one said reference value; or (4)(b)recommending or prescribing or initiating a treatment regimen notcomprising chemotherapy and/or a synthetic lethality agent based atleast in part on said comparing step revealing that the test value isnot greater (e.g., not more than 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or10-fold greater; not more than 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standarddeviations greater) than at least one said reference value. Theinvention encompasses, mutatis mutandis, corresponding embodiments wherethe test value or score is used to determine the patient's prognosis,the patient's likelihood of response to a particular treatment regimen,the patient's or patient's sample's likelihood of having a BRCA1, BRCA2,RAD51C or HDR deficiency, etc.

In one aspect, the invention provides a kit comprising, in a container,reagents suitable for determining allelic imbalance in at least 1, 2, 3,4, 5, 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 400, 500, 750,1,000, 1,500, 2,000, 2,500, 3,000, 4,000, 5,000, 7,500, or 10,000 ormore telomeric loci (e.g., loci within 50 Kb, 100 Kb, 200 Kb, 300 Kb,400 Kb, 500 Kb, 750 Kb, 1 Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb,9 Mb, or 10 Mb of the telomere). In some embodiments the kit comprisesreagents for determining allelic imbalance in no more than 10,000,7,500, 5,000, 4,000, 3,000, 2,000, 1,000, 750, 500, 400, 300, 200, 150,100, 90, 80, 70, 60, or 50 total loci. In some embodiments telomericloci comprise at least 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%,95%, 99%, or 100% of the loci for which the kit contains reagents fordetermining allelic imbalance.

As discussed above, allelic imbalance is a type of chromosomalaberration. As used herein, “allelic imbalance” means a change in thenumber and/or type of alleles of a chromosome in a somatic tissue ascompared to germline. In some embodiments allelic imbalance is loss ofheterozygosity (“LOH”). This can be copy number neutral, such as whenone of the heterozygous parental alleles is lost and the other allele isduplicated as a “replacement.” LOH can also occur in a non-copy numberneutral way, where one parental allele is simply lost. In someembodiments allelic imbalance is duplication of one allele over another(somatic AA/B from AA/B germline) or greater duplication of one alleleas compared to another (e.g., somatic AAAA/BB from A/B germline). Insome embodiments a region has allelic imbalance if loci in that regionshow MCP (as discussed in greater detail in Section IV.H. below) of isgreater than 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.60,0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.69, 0.70, 0.71, 0.72,0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.80. 0.81, 0.82, 0.83, 0.84,0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.92, 0.93, 0.94, 0.95,0.96, 0.97, 0.98, or 0.99 (including MCP of 1).

Thus, a predefined number of chromosomes may be analyzed to determinethe total number of Indicator LOH Regions, preferably the total numberof LOH regions of a length of greater than 9 megabases, 10 megabases, 12megabases, 14 megabases, more preferably greater than 15 megabases.Alternatively or in addition, the sizes of all identified Indicator LOHRegions may be summed up to obtain a total length of Indicator LOHRegions.

For classification of positive LOH signature status, the referencenumber discussed above for the total number of Indicator LOH Regions maybe 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20 or greater,preferably 5, preferably 8, more preferably 9 or 10, most preferably 10.The reference number for the total (e.g., combined) length of IndicatorLOH Regions may be about 75, 90, 105, 120, 130, 135, 150, 175, 200, 225,250, 275, 300, 325 350, 375, 400, 425, 450, 475, 500 megabases orgreater, preferably about 75 megabases or greater, preferably about 90or 105 megabases or greater, more preferably about 120 or 130 megabasesor greater, and more preferably about 135 megabases or greater, and mostpreferably about 150 megabases or greater.

In some specific embodiments, the total number of LOH regions of alength of greater than about 14 or 15 megabases is determined andcompared to a reference number of about 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 18, 19, or 20. Alternatively or in addition, the totallength of LOH regions of a length of greater than about 14 or 15megabases is determined and compared to a reference number of about 75,90, 105, 120, 130, 135, 150, 175, 200, 225, 250, 275, 300, 325 350, 375,400, 425, 450, 475, or 500 megabases.

In some embodiments, the number of LOH regions (or the combined length,or a test value or score derived from either) in a patient sample isconsidered “greater” than a reference if it is at least 2-, 3-, 4-, 5-,6-, 7-, 8-, 9-, or 10-fold greater than the reference while in someembodiments, it is considered “greater” if it is at least 1, 2, 3, 4, 5,6, 7, 8, 9, or 10 standard deviations greater than the reference.Conversely, in some embodiments the number of LOH regions (or thecombined length, or a test value or score derived from either) in apatient sample is considered “not greater” than a reference if it is notmore than 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater than thereference while in some embodiments, it is considered “not greater” ifit is not more than 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standard deviationsgreater than the reference.

In some embodiments the reference number (or length, value or score) isderived from a relevant reference population. Such reference populationsmay include patients (a) with the same cancer as the patient beingtested, (b) with the same cancer sub-type, (c) with cancer havingsimilar genetic or other clinical or molecular features, (d) whoresponded to a particular treatment, (e) who did not respond to aparticular treatment, (f) who are apparently healthy (e.g., do not haveany cancer or at least do not have the tested patient's cancer), etc.The reference number (or length, value or score) may be (a)representative of the number (or length, value or score) found in thereference population as a whole, (b) an average (mean, median, etc.) ofthe number (or length, value or score) found in the reference populationas a whole or a particular sub-population, (c) representative of thenumber (or length, value or score) (e.g., an average such as mean ormedian) found in terciles, quartiles, quintiles, etc. of the referencepopulation as ranked by (i) their respective number (or length, value orscore) or (ii) the clinical feature they were found to have (e.g.,strength of response, prognosis (including time to cancer-specificdeath), etc.).

As described herein, patients having cancer cells identified as having apositive LOH signature status or increase in the NAI or NtAI can beclassified, based at least in part on a positive LOH signature status orincrease in the NAI or NtAI, as being likely to respond to a particularcancer treatment regimen. For example, patients having cancer cells witha genome containing an LOH signature or increase in the NAI or NtAI canbe classified, based at least in part on a positive LOH signature statusor increase in the NAI or NtAI, as being likely to respond to a cancertreatment regimen that includes the use of a DNA damaging agent, asynthetic lethality agent (e.g., a PARP inhibitor), radiation, or acombination thereof. Preferably the patients are treatment naïvepatients.

Examples of DNA damaging agents include, without limitation,platinum-based chemotherapy drugs (e.g., cisplatin, carboplatin,oxaliplatin, and picoplatin), anthracyclines (e.g., epirubicin anddoxorubicin), topoisomerase I inhibitors (e.g., campothecin, topotecan,and irinotecan), DNA crosslinkers such as mitomycin C, and triazenecompounds (e.g., dacarbazine and temozolomide). Synthetic lethalitytherapeutic approaches typically involve administering an agent thatinhibits at least one critical component of a biological pathway that isespecially important to a particular tumor cell's survival. For example,when a tumor cell has a deficient homologous repair pathway (e.g., asdetermined according to the present invention), inhibitors of poly ADPribose polymerase (or platinum drugs, double strand break repairinhibitors, etc.) can be especially potent against such tumors becausetwo pathways critical to survival become obstructed (one biologically,e.g., by BRCA1 mutation, and the other synthetically, e.g., byadministration of a pathway drug). Synthetic lethality approaches tocancer therapy are described in, e.g., O'Brien et al., Converting cancermutations into therapeutic opportunities, EMBO MOL. MED. (2009)1:297-299.

Examples of synthetic lethality agents include, without limitation, PARPinhibitors or double strand break repair inhibitors in homologousrepair-deficient tumor cells, PARP inhibitors in PTEN-deficient tumorcells, methotrexate in MSH2-deficient tumor cells, etc. Examples of PARPinhibitors include, without limitation, olaparib, iniparib, andveliparib. Examples of double strand break repair inhibitors include,without limitation, KU55933 (ATM inhibitor) and NU7441 (DNA-PKcsinhibitor). Examples of information that can be used in addition to apositive LOH signature status to base a classification of being likelyto respond to a particular cancer treatment regimen include, withoutlimitation, previous treatment results, germline or somatic DNAmutations, gene or protein expression profiling (e.g., ER/PR/HER2status, PSA levels), tumor histology (e.g., adenocarcinoma, squamouscell carcinoma, papillary serous carcinoma, mucinous carcinoma, invasiveductal carcinoma, ductal carcinoma in situ (non-invasive), etc.),disease stage, tumor or cancer grade (e.g., well, moderately, or poorlydifferentiated (e.g., Gleason, modified Bloom Richardson), etc.), numberof previous courses of treatment, etc.

In addition to predicting likely treatment response or selectingdesirable treatment regimens, an LOH signature or increase in the NAI orNtAI can be used to determine a patient's prognosis. We have shown thatpatients whose tumors have an LOH signature or increase in the NAI orNtAI show significantly better survival than patients whose tumors donot have such an LOH signature or increase in the NAI or NtAI Thus, inone aspect, this document features a method for determining a patient'sprognosis based at least in part of detecting the presence or absence ofan LOH signature or increase in the NAI or NtAI in a sample from thepatient. The method comprises, or consists essentially of, (a)determining whether the patient comprises cancer cells having an LOHsignature or increase in the NAI or NtAI as described herein (e.g.,wherein the presence of more than a reference number of LOH regions inat least one pair of human chromosomes of a cancer cell of the cancerpatient that are longer than a first length but shorter than the lengthof the whole chromosome containing the LOH region or AI or tAI regionindicates that the cancer cells have the LOH signature or increase inthe NAI or NtAI, wherein the at least one pair of human chromosomes isnot a human X/Y sex chromosome pair, wherein the first length is about1.5 or more megabases), and (b)(1) determining, based at least in parton the presence of the LOH signature or or increase in the NAI or NtAI,that the patient has a relatively good prognosis, or (b)(2) determining,based at least in part on the absence of the LOH signature or increasein the NAI or NtAI, that the patient has a relatively poor prognosis.

Prognosis may include the patient's likelihood of survival (e.g.,progression-free survival, overall survival), wherein a relatively goodprognosis would include an increased likelihood of survival as comparedto some reference population (e.g., average patient with this patient'scancer type/subtype, average patient not having an LOH signature orincrease in the NAI or NtAI, etc.). Conversely, a relatively poorprognosis in terms of survival would include a decreased likelihood ofsurvival as compared to some reference population (e.g., average patientwith this patient's cancer type/subtype, average patient having an LOHsignature or increase in the NAI or NtAI, etc.).

“Telomeric allelic imbalance” means allelic imbalance in a telomericregion or segment. “Allelic imbalance” in a region or a “region ofallelic imbalance” means allelic imbalance in at least some number ofloci defining (in whole or in part) such region. These are generally tobe distinguished from isolated loci of allelic imbalance. Thus, in someembodiments regions of allelic imbalance are defined as at least 2, 3,4, 5, 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 400, 500, or moreconsecutive probes showing allelic imbalance.

The number or proportion of telomeric regions having allelic imbalancecan be used to derive a telomeric allelic imbalance score (sometimesreferred to herein as NtAI), which is analogous to the chromosomalaberration score described above (including the GCAS) and particularlybelow, though focused on telomeric regions. Thus, in some embodimentsthe invention provides a method of deriving a telomeric allelicimbalance score comprising: determining whether a sample has achromosomal aberration (e.g., of allelic imbalance, loss ofheterozygosity, copy number aberrations, copy number gain, copy numberdecrease) at a plurality of assay (e.g., genomic) loci; analyzing aplurality of test loci within said plurality of assay loci forchromosomal aberrations; combining the data from (2) to derive a scorereflecting the overall extent of chromosomal aberration in saidplurality of test loci, thereby deriving a chromosomal aberration score.

In some embodiments, the data are combined in (3) in such a way thateach test locus is assigned a weighting coefficient that determines itscontribution to the chromosomal aberration score and telomeric loci areweighted such that they contribute at least 5% (or 10%, or 15%, or 20%,or 30%, or 40%, or 50%, or 60%, or 70%, or 80%, or 90%, or 95%, or 100%)to the chromosomal aberration score. In some embodiments, at least 5%(or 10%, or 15%, or 20%, or 30%, or 40%, or 50%, or 60%, or 70%, or 80%,or 90%, or 95%, or 100%) of the test loci in (2) are telomeric loci.

In some embodiments the telomeric allelic imbalance score will count alltelomeric regions showing allelic imbalance. In some embodiments thiswill include regions of allelic imbalance that encompass an entirechromosome. In some embodiments the telomeric allelic imbalance scorewill count all telomeric regions of at least some minimum size (e.g., 1Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, 10 Mb, 11 Mb, 12 Mb,13 Mb, 14 Mb, 15 Mb, 16 Mb, 17 Mb, 18 Mb, 19 Mb, 20 Mb, 21 Mb, 22 Mb, 23Mb, 24 Mb, 25 Mb, or more, or any range in between, such as between 5and 25 Mb) showing allelic imbalance.

In some embodiments, at least 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, 75, or100 or more telomeric regions with allelic imbalance (e.g., a hightelomeric allelic imbalance score (e.g., a score of at least 1, 2, 3, 4,5, 10, 15, 20, 22, 23, 23.5, 24, 25, 26, 27, 50, 75, or 100 or more))indicates an increased likelihood of response to therapy comprising aparticular modality (e.g., platinum compounds, cytotoxic antibiotics,antimetabolities, anti-mitotic agents, alkylating agents, arseniccompounds, DNA topoisomerase inhibitors, taxanes, nucleoside analogues,plant alkaloids, and toxins; cisplatin, treosulfan, and trofosfamide;plant alkaloids: vinblastine, paclitaxel, docetaxol; DNA topoisomeraseinhibitors: teniposide, crisnatol, and mitomycin; anti-folates:methotrexate, mycophenolic acid, and hydroxyurea; pyrimidine analogs:5-fluorouracil, doxifluridine, and cytosine arabinoside; purine analogs:mercaptopurine and thioguanine; DNA antimetabolites:2′-deoxy-5-fluorouridine, aphidicolin glycinate, and pyrazoloimidazole;and antimitotic agents: halichondrin, colchicine, and rhizoxin; andsynthetic derivatives thereof).

Thus, in some embodiments the invention provides a method of predictingwhether a patient will respond to a particular treatment comprising:determining whether a sample has a chromosomal aberration (e.g., ofallelic imbalance, loss of heterozygosity, copy number aberrations, copynumber gain, copy number decrease) at a plurality of assay (e.g.,genomic) loci; analyzing a plurality of test loci within said pluralityof assay loci for chromosomal aberrations; combining the data from (2)to derive a chromosomal aberration score reflecting the overall extentof chromosomal aberration in said plurality of test loci; correlating ahigh chromosomal aberration score to increased likelihood of response toa particular treatment.

In some embodiments, the data are combined in (3) in such a way thateach test locus is assigned a weighting coefficient that determines itscontribution to the chromosomal aberration score and telomeric loci areweighted such that they contribute at least 5% (or 10%, or 15%, or 20%,or 30%, or 40%, or 50%, or 60%, or 70%, or 80%, or 90%, or 95%, or 100%)to the chromosomal aberration score. In some embodiments, at least 5%(or 10%, or 15%, or 20%, or 30%, or 40%, or 50%, or 60%, or 70%, or 80%,or 90%, or 95%, or 100%) of the test loci in (2) are telomeric loci. Insome embodiments the telomeric allelic imbalance score will count alltelomeric regions showing allelic imbalance. In some embodiments thiswill include regions of allelic imbalance that encompass an entirechromosome. In some embodiments the telomeric allelic imbalance scorewill count all telomeric regions of at least some minimum size (e.g., 1Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, 10 Mb, 11 Mb, 12 Mb,13 Mb, 14 Mb, 15 Mb, 16 Mb, 17 Mb, 18 Mb, 19 Mb, 20 Mb, 21 Mb, 22 Mb, 23Mb, 24 Mb, 25 Mb, or more, or any range in between, such as between 5and 25 Mb) showing allelic imbalance. In some embodiments, a telomericallelic imbalance score is high if at least 1, 2, 3, 4, 5, 10, 15, 20,25, 50, 75, or 100 or more telomeric regions have allelic imbalance.

Heterozygous SNPs can be used in the methods of the invention todetermine the phenotype of a cancer are informative, meaningheterozygosity is observed in the nucleic acid sample from non-canceroustissue and/or cells of a subject. According to the methods of theinvention, these informative SNPs are examined in the nucleic acidsample from a cancerous tissue and/or cells of a subject to determineGCAS. In a further embodiment, the nucleic acid samples used todetermine the number of heterozygous SNPs in the plurality of SNPs, thatexhibit heterozygosity in genomic DNA of non-cancerous tissue of thespecies to which the cancer patient belongs, are taken from at least 1,2, 5, 10, 20, 30, 40, 50, 100, or 250 different organisms of thatspecies. A skilled artisan will understand that appropriate controls canbe determined based upon the average frequency of SNP alleles that existwithin the same ethnic group of the species to which the patientbelongs. In certain embodiments, the informative SNPs used in themethods of the invention to determine and/or predict the phenotype of acancer comprise at least one SNP on each chromosome of a subject (e.g.,a telomeric region of each chromosome). In a related embodiment, theinformative SNPs used in the methods of the invention to determineand/or predict the phenotype of a cancer comprise at least one SNP oneach arm of each chromosome of a subject (e.g., a telomeric region ofeach arm of each chromosome).

In certain embodiments, the invention provides methods for determiningthe phenotype of a cancer wherein the phenotype is response to therapy.The therapy may be any anti-cancer therapy including, but not limitedto, chemotherapy, radiation therapy, immunotherapy, small moleculeinhibitors, shRNA, hormonal, and combinations thereof. Where GCASrepresents copy deletions, copy gains, whole chromosome losses, wholechromosome gains and/or loss of heterozygosity, subjects whose canceroustissue exhibit a GCAS below a threshold value are predicted to have apoorer response to therapy (e.g., radiation or chemotherapy) than thosewith high GCAS (above the threshold value). Where GCAS represents lackof copy or chromosome number changes and/or retention of heterozygosity,subjects whose cancerous tissue exhibits a GCAS above a threshold valueare predicted to have a poorer response to therapy (e.g., radiation orchemotherapy) than those with low GCAS (below the threshold value).

By way of explanation, but without being bound by theory, it is believedthat where the GCAS value represents loss of heterozygosity or allelicimbalance, it identifies cells harboring improperly repaired chromosomalDNA double-strand breaks and the genome-wide count of these chromosomalrearrangements in a specific tumor indicates the degree of DNA repairincompetence, independent of the specific causative DNA repair defect.In such subjects, the total number of chromosomal rearrangements in atumor indicates the inability to repair DNA damage induced byanti-cancer therapies, and consequently predicts sensitivity to suchanti-cancer therapies. Also by way of explanation and without beingbound by theory, it is believed that GCAS representing copy gains mayindicate genetic defects other than or in addition to DNA repair defectsand that GCAS representing whole chromosome loss or gain may indicatemitotic checkpoint defects or chromosome segregation defects, and thelike. Such aberrations in faithful DNA repair, segregation, check pointcontrol, etc. has been determined to be predictive of the cellsharboring such aberrations to treatment with anti-cancer therapies(e.g., chemotherapeutics) in subjects.

The response to anti-cancer therapies relates to any response of thetumour to chemotherapy, preferably to a change in tumour mass and/orvolume after initiation of neoadjuvant or adjuvant chemotherapy. Tumorresponse may be assessed in a neoadjuvant or adjuvant situation wherethe size of a tumour after systemic intervention can be compared to theinitial size and dimensions as measured by CT, PET, mammogram,ultrasound or palpation and the cellularity of a tumor can be estimatedhistologically and compared to the cellularity of a tumor biopsy takenbefore initiation of treatment. Response may also be assessed by calipermeasurement or pathological examination of the tumour after biopsy orsurgical resection. Response may be recorded in a quantitative fashionlike percentage change in tumour volume or cellularity or using asemi-quantitative scoring system such as residual cancer burden (Symmanset al., J. Clin. Oncol. (2007) 25:4414-5 4422) or Miller-Payne score(Ogston et al., Breast (Edinburgh, Scotland) (2003) 12:320-327) in aqualitative fashion like “pathological complete response” (pCR),“clinical complete remission” (cCR), “clinical partial remission” (cPR),“clinical stable disease” (cSD), “clinical progressive disease” (cPD) orother qualitative criteria. Assessment of tumor response may beperformed early after the onset of neoadjuvant or adjuvant therapy,e.g., after a few hours, days, weeks or preferably after a few months. Atypical endpoint for response assessment is upon termination ofneoadjuvant chemotherapy or upon surgical removal of residual tumorcells and/or the tumor bed.

Additional criteria for evaluating the response to anti-cancer therapiesare related to “survival,” which includes all of the following: survivaluntil mortality, also known as overall survival (wherein said mortalitymay be either irrespective of cause or tumor related); “recurrence-freesurvival” (wherein the term recurrence shall include both localized anddistant recurrence); metastasis free survival; disease free survival(wherein the term disease shall include cancer and diseases associatedtherewith). The length of said survival may be calculated by referenceto a defined start point (e.g. time of diagnosis or start of treatment)and end point (e.g. death, recurrence or metastasis). In addition,criteria for efficacy of treatment can be expanded to include responseto chemotherapy, probability of survival, probability of metastasiswithin a given time period, and probability of tumor recurrence.

For example, in order to determine appropriate threshold values, aparticular anti-cancer therapeutic regimen can be administered to apopulation of subjects and the outcome can be correlated to GCAS's thatwere determined prior to administration of any anti-cancer therapy. Theoutcome measurement may be pathologic response to therapy given in theneo-adjuvant setting. Alternatively, outcome measures, such as overallsurvival and disease-free survival can be monitored over a period oftime for subjects following anti-30 cancer therapy for whom GCAS valuesare known. In certain embodiments, the same doses of anti-cancer agentsare administered to each subject. In related embodiments, the dosesadministered are standard doses known in the art for anti-cancer agents.The period of time for which subjects are monitored can vary. Forexample, subjects may be monitored for at least 2, 4, 6, 8, 10, 12, 14,16, 18, 20, 25, 30, 35, 40, 45, 50, 55, or 60 months. GCAS thresholdvalues that correlate to outcome of an anti-cancer therapy can bedetermined using methods such as those described in the Example section.

In some embodiments, the test value representing the chromosomalaberration score is compared to one or more reference values (or indexvalues), and optionally correlated to an increased (or not) likelihoodof response to a particular treatment. For example, the index value mayrepresent the average chromosomal aberration score for a set ofindividuals from a diverse cancer population or a subset of thepopulation. For example, one may determine the average chromosomalaberration score in a random sampling of patients with cancer (or aparticular cancer). This average chromosomal aberration score may betermed the “threshold index value,” with patients having a chromosomalaberration score higher than this value expected to have a higherlikelihood of response than those having a chromosomal aberration scorelower than this value. In some embodiments the test value is correlatedto an increased likelihood of response to a particular treatment if thetest value exceeds the reference value by at least some amount (e.g., atleast 0.5, 0.75, 0.85, 0.90, 0.95, 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 ormore fold or standard deviations)

Alternatively the index value may represent the average chromosomalaberration score in a plurality of training patients with similaroutcomes whose clinical and follow-up data are available and sufficientto define and categorize the patients by outcome, e.g., response to aparticular treatment. See, e.g., Examples, infra. For example, a“response index value” can be generated from a plurality of trainingcancer patients characterized as having “response” to the particulartreatment. A “no (or poor) response index value” can be generated from aplurality of training cancer patients defined as having “no (or poor)response” to the particular treatment. Thus, a response prognosis indexvalue may represent the average chromosomal aberration score in patientshaving “response,” whereas a no (or poor) response index valuerepresents the average chromosomal aberration score in patients havingno or poor response. Thus, when the determined chromosomal aberrationscore is closer to the response index value than to the no responseindex value, then it can be concluded that the patient is more likely torespond. On the other hand, if the determined 1 chromosomal aberrationscore is closer to the no response index value than to the responseindex value, then it can be concluded that the patient does not have anincreased likelihood of response.

Prognosis may include the patient's likelihood of survival (e.g.,progression-free survival, overall survival), wherein a relatively goodprognosis would include an increased likelihood of survival as comparedto some reference population (e.g., average patient with this patient'scancer type/subtype, average patient not having an LOH signature,patient not having increased number of AI or tAI etc.). Conversely, arelatively poor prognosis in terms of survival would include a decreasedlikelihood of survival as compared to some reference population (e.g.,average patient with this patient's cancer type/subtype, average patienthaving an LOH signature, patient not having increased number of AI ortAI etc.).

Anti-Cancer Therapeutic Agents

The efficacy of anti-cancer therapies which damage DNA, as well asagents that take advantage of DNA repair defects but do not damage DNAthemselves, such as poly ADP ribose polymerase (PARP) inhibitors, aswell as chemotherapy or radiation therapy, is predicted according to theGCAS level of a cancer in a subject according to the methods describedherein. In one embodiment, the efficacy of chemotherapies is predicted.Chemotherapy includes the administration of a chemotherapeutic agent.Such a chemotherapeutic agent may be, but is not limited to, thoseselected from among the following groups of compounds: platinumcompounds, cytotoxic antibiotics, antimetabolities, anti-mitotic agents,alkylating agents, arsenic compounds, DNA topoisomerase inhibitors,taxanes, nucleoside analogues, plant alkaloids, and toxins; andsynthetic derivatives thereof. Exemplary compounds include, but are notlimited to, alkylating agents: cisplatin, treosulfan, and trofosfamide;plant alkaloids: vinblastine, paclitaxel, docetaxol; DNA topoisomeraseinhibitors: teniposide, crisnatol, and mitomycin; anti-folates:methotrexate, mycophenolic acid, and hydroxyurea; pyrimidine analogs:5-fluorouracil, doxifluridine, and cytosine arabinoside; purine analogs:mercaptopurine and thioguanine; DNA antimetabolites:2′-deoxy-5-fluorouridine, aphidicolin glycinate, and pyrazoloimidazole;and antimitotic agents: halichondrin, colchicine, and rhizoxin.Compositions comprising one or more chemotherapeutic agents (e.g., FLAG,CHOP) may also be used. FLAG comprises fludarabine, cytosine arabinoside(Ara-C) and G-CSF. CHOP comprises cyclophosphamide, vincristine,doxorubicin, and prednisone. In another embodiments, PARP (e.g., PARP-1and/or PARP-2) inhibitors are used and such inhibitors are well knowni nthe art (e.g., Olaparib, ABT-888, BSI-201, BGP-15 (N-Gene ResearchLaboratories, Inc.); INO-1001 (Inotek Pharmaceuticals Inc.); PJ34(Soriano et al., 2001; Pacher et al., 2002b); 3-aminobenzamide(Trevigen); 4-amino-1,8-naphthalimide; (Trevigen);6(5H)-phenanthridinone (Trevigen); benzamide (U.S. Pat. Re. 36,397); andNU1025 (Bowman et al.). The foregoing examples of chemotherapeuticagents are illustrative, and are not intended to be limiting.

In a preferred embodiment, the chemotherapeutic agents are platinumcompounds or platinum-comprising cancer therapies, such as cisplatin,carboplatin, oxaliplatin, nedaplatin, and iproplatin. Otherantineoplastic platinum coordination compounds are well known in theart, can be modified according to well-known methods in the art, andinclude the compounds disclosed in U.S. Pat. Nos. 4,996,337, 4,946,954,5,091,521, 5,434,256, 5,527,905, and 5,633,243, all of which areincorporated herein by reference. In another embodiment, GCAS predictsefficacy of radiation therapy. The radiation used in radiation therapycan be ionizing radiation. Radiation therapy can also be gamma rays,X-rays, or proton beams. Examples of radiation therapy include, but arenot limited to, external-beam radiation therapy, interstitialimplantation of radioisotopes (1-125, palladium, iridium), radioisotopessuch as strontium-89, thoracic radiation therapy, intraperitoneal P-32radiation therapy, and/or total abdominal and pelvic radiation therapy.For a general overview of radiation therapy, see Hellman, Chapter 16:Principles of Cancer Management: Radiation Therapy, 6th edition, 2001,DeVita et al., eds., J. B. Lippencott Company, Philadelphia. Theradiation therapy can be administered as external beam radiation orteletherapy wherein the radiation is directed from a remote source. Theradiation treatment can also be administered as internal therapy orbrachytherapy wherein a radioactive source is placed inside the bodyclose to cancer cells or a tumor mass. Also encompassed is the use ofphotodynamic therapy comprising the administration of photosensitizers,such as hematoporphyrin and its derivatives, Vertoporfin (BPD-MA),phthalocyanine, photosensitizer Pc4, demethoxy-hypocrellin A; and2BA-2-DMHA.

Anti-cancer therapies which damage DNA to a lesser extent thanchemotherapy or radiation therapy may have efficacy in subjectsdetermined to have relatively lower or higher GCAS determinations usingthe methods of the invention for determining the phenotype of a cancer.Examples of such therapies include immunotherapy, hormone therapy, andgene therapy. Such therapies include, but are not limited to, the use ofantisense polynucleotides, ribozymes, RNA interference molecules, triplehelix polynucleotides and the like, where the nucleotide sequence ofsuch compounds are related to the nucleotide sequences of DNA and/or RNAof genes that are linked to the initiation, progression, and/orpathology of a tumor or cancer. For example, oncogenes, growth factorgenes, growth factor receptor genes, cell cycle genes, DNA repair genes,and others, may be used in such therapies.

Immunotherapy may comprise, for example, use of cancer vaccines and/orsensitized antigen presenting cells. The immunotherapy can involvepassive immunity for short-term protection of a host, achieved by theadministration of pre-formed antibody directed against a cancer antigenor disease antigen (e.g., administration of a monoclonal antibody,optionally linked to a chemotherapeutic agent or toxin, to a tumorantigen). Immunotherapy can also focus on using the cytotoxiclymphocyte-recognized epitopes of cancer cell lines.

Hormonal therapeutic treatments can comprise, for example, hormonalagonists, hormonal antagonists (e.g., flutamide, bicalutamide,tamoxifen, raloxifene, leuprolide acetate (LUPRON), LH-RH antagonists),inhibitors of hormone biosynthesis and processing, and steroids (e.g.,dexamethasone, retinoids, deltoids, betamethasone, cortisol, cortisone,prednisone, dehydrotestosterone, glucocorticoids, mineralocorticoids,estrogen, testosterone, progestins), vitamin A derivatives (e.g.,all-trans retinoic acid (ATRA)); vitamin D3 analogs; antigestagens(e.g., mifepristone, onapristone), or antiandrogens (e.g., cyproteroneacetate).

In one embodiment, anti-cancer therapy used for cancers whose phenotypeis determined by the methods of the invention can comprise one or moretypes of therapies described herein including, but not limited to,chemotherapeutic agents, immunotherapeutics, anti-angiogenic agents,cytokines, hormones, antibodies, polynucleotides, radiation andphotodynamic therapeutic agents. For example, combination therapies cancomprise one or more chemotherapeutic agents and radiation, one or morechemotherapeutic agents and immunotherapy, or one or morechemotherapeutic agents, radiation and chemotherapy.

The duration and/or dose of treatment with anti-cancer therapies mayvary according to the particular anti-cancer agent or combinationthereof. An appropriate treatment time for a particular cancertherapeutic agent will be appreciated by the skilled artisan. Theinvention contemplates the continued assessment of optimal treatmentschedules for each cancer therapeutic agent, where the phenotype of thecancer of the subject as determined by the methods of the invention is afactor in determining optimal treatment doses and schedules.

Cancers for which Phenotype can be Determined

The methods of the invention can be used to determine the phenotype ofmany different cancers. Specific examples of types of cancers for whichthe phenotype can be determined by the methods encompassed by theinvention include, but are not limited to, human sarcomas andcarcinomas, e.g., fibrosarcoma, myxosarcoma, liposarcoma,chondrosarcoma, osteogenic sarcoma, chordoma, angiosarcoma,endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma,synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma,rhabdomyosarcoma, colon carcinoma, colorectal cancer, pancreatic cancer,breast cancer, ovarian cancer, prostate cancer, squamous cell carcinoma,basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceousgland carcinoma, papillary carcinoma, papillary adenocarcinomas,cystadenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renalcell carcinoma, hepatoma, bile duct carcinoma, liver cancer,choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, cervicalcancer, bone cancer, brain tumor, testicular cancer, lung carcinoma,small cell lung carcinoma, bladder carcinoma, epithelial carcinoma,glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma,pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma,meningioma, melanoma, neuroblastoma, retinoblastoma; leukemias, e.g.,acute lymphocytic leukemia and acute myelocytic leukemia (myeloblastic,promyelocytic, myelomonocytic, monocytic and erythroleukemia); chronicleukemia (chronic myelocytic (granulocytic) leukemia and chroniclymphocytic leukemia); and polycythemia vera, lymphoma (Hodgkin'sdisease and non-Hodgkin's disease), multiple myeloma, Waldenstrom'smacroglobulinemia, and heavy chain disease.

In some embodiments, the cancer cells are primary or metastatic cancercells of ovarian cancer, breast cancer, lung cancer or esophagealcancer.

In some embodiments, the cancer whose phenotype is determined by themethod of the invention is an epithelial cancer such as, but not limitedto, bladder cancer, breast cancer, cervical cancer, colon cancer,gynecologic cancers, renal cancer, laryngeal cancer, lung cancer, oralcancer, head and neck cancer, ovarian cancer, pancreatic cancer,prostate cancer, or skin cancer. In other embodiments, the cancer isbreast cancer, prostate cancer, lung cancer, or colon cancer. In stillother embodiments, the epithelial cancer is non-small-cell lung cancer,nonpapillary renal cell carcinoma, cervical carcinoma, ovarian carcinoma(e.g., serous ovarian carcinoma), or breast carcinoma. The epithelialcancers may be characterized in various other ways including, but notlimited to, serous, endometrioid, mucinous, clear cell, brenner, orundifferentiated.

Subjects

In one embodiment, the subject for whom predicted efficacy of ananti-cancer therapy is determined, is a mammal (e.g., mouse, rat,primate, non-human mammal, domestic animal such as dog, cat, cow,horse), and is preferably a human. In another embodiment of the methodsof the invention, the subject has not undergone chemotherapy orradiation therapy. In alternative embodiments, the subject has undergonechemotherapy or radiation therapy (e.g., such as with cisplatin,carboplatin, and/or taxane). In related embodiments, the subject has notbeen exposed to levels of radiation or chemotoxic agents above thoseencountered generally or on average by the subjects of a species. Incertain embodiments, the subject has had surgery to remove cancerous orprecancerous tissue. In other embodiments, the cancerous tissue has notbeen removed, e.g., the cancerous tissue may be located in an inoperableregion of the body, such as in a tissue that is essential for life, orin a region where a surgical procedure would cause considerable risk ofharm to the patient.

In some embodiments, the patients are treatment naïve patients.

According to one aspect of the invention, GCAS can be used to determinethe phenotype, i.e. responsiveness to therapy of a cancer in a subject,where the subject has previously undergone chemotherapy, radiationtherapy, or has been exposed to radiation, or a chemotoxic agent. Suchtherapy or exposure could potentially damage DNA and alter the numbersof informative heterozygous SNPs in a subject. The altered number ofinformative heterozygous SNPs would in turn alter the GCAS of a subject.Because the non-cancerous DNA samples would exhibit greater or fewerheterozygous SNPs, the range of GCASs would be altered for a populationof subjects. In certain embodiments, DNA damage from therapy or exposurein a subject or population of subjects occurs about 1 month, 2 months, 3months, 4 months, 5 months, 6 months, 7 months, 8 months, 9 months, 10months, 11 months, 1 year, 1.5 years, 2 years or more beforedetermination of GCAS. To determine GCAS threshold values for subjectsthat exhibit DNA damage from therapy or exposure, a population ofsubjects is monitored who have had chemotherapy or radiation therapy,preferably via identical or similar treatment regimens, including doseand frequency, for said subjects.

Nucleic Acid Sample Preparation

Nucleic Acid Isolation

Nucleic acid samples derived from cancerous and non-cancerous cells of asubject that can be used in the methods of the invention to determinethe phenotype of a cancer can be prepared by means well known in theart. For example, surgical procedures or needle biopsy aspiration can beused to collect cancerous samples from a subject. In some embodiments,it is important to enrich and/or purify the cancerous tissue and/or cellsamples from the non-cancerous tissue and/or cell samples. In otherembodiments, the cancerous tissue and/or cell samples can then bemicrodissected to reduce amount of normal tissue contamination prior toextraction of genomic nucleic acid or pre-RNA for use in the methods ofthe invention. In still another embodiment, the cancerous tissue and/orcell samples are enriched for cancer cells by at least 50%, 55%, 60%,65%, 70%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%,87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or moreor any range in between, in cancer cell content. Such enrichment can beaccomplished according to methods well-15 known in the art, such asneedle microdissection, laser microdissection, fluorescence activatedcell sorting, and immunological cell sorting. In one embodiment, anautomated machine performs the hyperproliferative cell enrichment tothereby transform the biological sample into a purified form enrichedfor the presence of hyperproliferative cells.

Collecting nucleic acid samples from non-cancerous cells of a subjectcan also be accomplished with surgery or aspiration. In surgicalprocedures where cancerous tissue is removed, surgeons often removenon-cancerous tissue and/or cell samples of the same tissue type of thecancer patient for comparison. Nucleic acid samples can be isolated fromsuch non-cancerous tissue of the subject for use in the methods of theinvention. In certain embodiments of the methods of the invention,nucleic acid samples from non-cancerous tissues are not derived from thesame tissue type as the cancerous tissue and/or cells sampled, and/orare not derived from the cancer patient. The nucleic acid samples fromnon-cancerous tissues may be derived from any non-cancerous and/ordisease-free tissue and/or cells. Such non-cancerous samples can becollected by surgical or non-surgical procedures. In certainembodiments, non-cancerous nucleic acid samples are derived fromtumor-free tissues. For example, non-cancerous samples may be collectedfrom lymph nodes, peripheral blood lymphocytes, and/or mononuclear bloodcells, or any subpopulation thereof. In a preferred embodiment, thenon-cancerous tissue is not pre-cancerous tissue, e.g., it does notexhibit any indicia of a pre-neoplastic condition such as hyperplasia,metaplasia, or dysplasia.

In one embodiment, the nucleic acid samples used to compute GCAS (e.g.,the number of heterozygous SNPs in the plurality of total SNPs thatexhibit heterozygosity in genomic DNA of non-cancerous tissue of thespecies to which the cancer patient belongs) are taken from at least 1,2, 5, 10, 20, 30, 40, 50, 100, or 200 different organisms of thatspecies. According to certain aspects of the invention, nucleic acid“derived from” genomic DNA, as used in the methods of the invention,e.g., in hybridization experiments to determine heterozygosity of SNPs,can be fragments of genomic nucleic acid generated by restriction enzymedigestion and/or ligation to other nucleic acid, and/or amplificationproducts of genomic nucleic acids, or pre-messenger RNA (pre-mRNA),amplification products of pre-mRNA, or genomic DNA fragments grown up incloning vectors generated, e.g., by “shotgun” cloning methods. Incertain embodiments, genomic nucleic acid samples are digested withrestriction enzymes.

Amplification of Nucleic Acids

Though the nucleic acid sample need not comprise amplified nucleic acid,in some embodiments, the isolated nucleic acids can be processed inmanners requiring and/or taking advantage of amplification. The genomicDNA samples of a subject optionally can be fragmented using restrictionendonucleases and/or amplified prior to determining GCAS. In oneembodiment, the DNA fragments are amplified using polymerase chainreaction (PCR). Methods for practicing PCR are well known to those ofskill in the art. One advantage of PCR is that small quantities of DNAcan be used. For example, genomic DNA from a subject may be about 150ng, 175, ng, 200 ng, 225 ng, 250 ng, 275 ng, or 300 ng of DNA.

In certain embodiments of the methods of the invention, the nucleic acidfrom a subject is amplified using a single primer pair. For example,genomic DNA samples can be digested with restriction endonucleases togenerate fragments of genomic DNA that are then ligated to an adaptorDNA sequence which the primer pair recognizes. In other embodiments ofthe methods of the invention, the nucleic acid of a subject is amplifiedusing sets of primer pairs specific to loci of interest (e.g., RFLPs,STRs, SNPs, etc.) located throughout the genome. Such sets of primerpairs each recognize genomic DNA sequences flanking particular loci ofinterest (e.g., SNPs, RFLPs, STRs, etc.). A DNA sample suitable forhybridization can be obtained, e.g., by polymerase chain reaction (PCR)amplification of genomic DNA, fragments of genomic DNA, fragments ofgenomic DNA ligated to adaptor sequences or cloned sequences. Computerprograms that are well known in the art can be used in the design ofprimers with the desired specificity and optimal amplificationproperties, such as Oligo version 5.0 (National Biosciences). PCRmethods are well known in the art, and are described, for example, inInnis et al., eds., 1990, PCR Protocols: A Guide to Methods AndApplications, Academic Press Inc., San Diego, Calif. It will be apparentto one skilled in the art that controlled robotic systems are useful forisolating and amplifying nucleic acids and can be used.

In other embodiments, where genomic DNA of a subject is fragmented usingrestriction endonucleases and amplified prior to determining GCAS, theamplification can comprise cloning regions of genomic DNA of thesubject. In such methods, amplification of the DNA regions is achievedthrough the cloning process. For example, expression vectors can beengineered to express large quantities of particular fragments ofgenomic DNA of the subject (Sambrook, J. et al., eds., 1989, MolecularCloning: A Laboratory Manual, 2nd Ed., Cold Spring Harbor LaboratoryPress, Cold Spring Harbor, N.Y., at pp. 9.47-9.51).

In yet other embodiments, where the DNA of a subject is fragmented usingrestriction endonucleases and amplified prior to determining GCAS, theamplification comprises expressing a nucleic acid encoding a gene, or agene and flanking genomic regions of nucleic acids, from the subject.RNA (pre-messenger RNA) that comprises the entire transcript includingintrons is then isolated and used in the methods of the invention todetermine GCAS and the phenotype of a cancer. In certain embodiments, noamplification is required. In such embodiments, the genomic DNA, orpre-RNA, of a subject may be fragmented using restriction endonucleasesor other methods. The resulting fragments may be hybridized to SNPprobes. Typically, greater quantities of DNA are needed to be isolatedin comparison to the quantity of DNA or pre-mRNA needed where fragmentsare amplified. For example, where the nucleic acid of a subject is notamplified, a DNA sample of a subject for use in hybridization may beabout 400 ng, 500 ng, 600 ng, 700 ng, 800 ng, 900 ng, or 1000 ng of DNAor greater. Alternatively, in other embodiments, methods are used thatrequire very small amounts of nucleic acids for analysis, such as lessthan 400 ng, 300 ng, 200 ng, 100 ng, 90 ng, 85 ng, 80 ng, 75 ng, 70 ng,65 ng, 60 ng, 55 ng, 50 ng, or less, such as is used for molecularinversion probe (MIP) assays. These techniques are particularly usefulfor analyzing clinical samples, such as paraffin embedded formalin-fixedmaterial or small core needle biopsies, characterized as being readilyavailable but generally having reduced DNA quality (e.g., small,fragmented DNA) and/or not providing large amounts of nucleic acids.

Hybridization

The nucleic acid samples derived from a subject used in the methods ofthe invention can be hybridized to arrays comprising probes (e.g.,oligonucleotide probes) in order to identify informative loci ofinterest (e.g., SNPs, RFLPs, STRs, etc.). Hybridization can also be usedto determine whether the informative loci of interest (e.g., SNPs,RFLPs, STRs, etc.) identified exhibit chromosomal aberrations (e.g.,allelic imbalance, loss of heterozygosity, total copy number change,copy number gain, and copy number loss) in nucleic acid samples fromcancerous tissues and/or cells of the subject. In preferred embodiments,the probes used in the methods of the invention comprise an array ofprobes that can be tiled on a DNA chip (e.g., SNP oligonucleotideprobes). In some embodiments, heterozygosity of a SNP locus isdetermined by a method that does not comprise detecting a change in sizeof restriction enzyme-digested nucleic acid fragments. In otherembodiments, SNPs are analyzed to identify allelic imbalance.Hybridization and wash conditions used in the methods of the inventionare chosen so that the nucleic acid samples to be analyzed by theinvention specifically bind or specifically hybridize to thecomplementary oligonucleotide sequences of the array, preferably to aspecific array site, wherein its complementary DNA is located. In someembodiments, the complementary DNA can be completely matched ormismatched to some degree as used, for example, in Affymetrixoligonucleotide arrays such as those used to analyze SNPs in MIP assays.The single-stranded synthetic oligodeoxyribonucleic acid DNA probes ofan array may need to be denatured prior to contact with the nucleic acidsamples from a subject, e.g., to remove hairpins or dimers which formdue to self-complementary sequences.

Optimal hybridization conditions will depend on the length of the probesand type of nucleic acid samples from a subject. General parameters forspecific (i.e., stringent) hybridization conditions for nucleic acidsare described in Sambrook, J. et al., eds., 1989, Molecular Cloning: ALaboratory Manual, 2nd Ed., Cold Spring Harbor Laboratory Press, ColdSpring Harbor, N.Y., at pp. 9.47-9.51 and 11.55-11.61; Ausubel et al.,eds., 1989, Current Protocols in Molecules Biology, Vol. 1, GreenPublishing Associates, Inc., John Wiley & Sons, Inc., New York, at pp.2.10.1-2.10.16. Exemplary useful hybridization conditions are providedin, e.g., Tijessen, 1993, Hybridization With Nucleic Acid Probes,Elsevier Science Publishers B. V. and Kricka, 1992, Nonisotopic DNAProbe Techniques, Academic Press, San Diego, Calif.

Oligonucleotide Nucleic Acid Arrays

In some embodiments of the methods of the present invention, DNA arrayscan be used to determine whether nucleic acid samples exhibitchromosomal aberrations (e.g., allelic imbalance, loss ofheterozygosity, total copy number change, copy number gain, and copynumber loss) by measuring the level of hybridization of the nucleic acidsequence to oligonucleotide probes that comprise complementarysequences. Hybridization can be used to determine the presence orabsence of heterozygosity. Various formats of DNA arrays that employoligonucleotide “probes,” (i.e., nucleic acid molecules having definedsequences) are well known to those of skill in the art. Typically, a setof nucleic acid probes, each of which has a defined sequence, isimmobilized on a solid support in such a manner that each differentprobe is immobilized to a predetermined region. In certain embodiments,the set of probes forms an array of positionally-addressable binding(e.g., hybridization) sites on a support. Each of such binding sitescomprises a plurality of oligonucleotide molecules of a probe bound tothe predetermined region on the support. More specifically, each probeof the array is preferably located at a known, predetermined position onthe solid support such that the identity (i.e., the sequence) of eachprobe can be determined from its position on the array (i.e., on thesupport or surface). Microarrays can be made in a number of ways, ofwhich several are described herein. However produced, microarrays sharecertain characteristics, they are reproducible, allowing multiple copiesof a given array to be produced and easily compared with each other.

Numerous variations on nucleic acid arrays useful in the invention areknown in the art. These include Affymetrix 500K GeneChip array;Affymetrix OncoScan™ FFPE Express 2.0 Services (Formerly MIP CNServices), and the like.

Preferably, the microarrays are made from materials that are stableunder binding (e.g., nucleic acid hybridization) conditions. Themicroarrays are preferably small, e.g., between about 1 cm2 and 25 cm2,preferably about 1 to 3 cm2. However, both larger and smaller arrays arealso contemplated and may be preferable, e.g., for simultaneouslyevaluating a very large number of different probes. Oligonucleotideprobes can be synthesized directly on a support to form the array. Theprobes can be attached to a solid support or surface, which may be made,e.g., from glass, plastic (e.g., polypropylene, nylon), polyacrylamide,nitrocellulose, gel, or other porous or nonporous material. The set ofimmobilized probes or the array of immobilized probes is contacted witha sample containing labeled nucleic acid species so that nucleic acidshaving sequences complementary to an immobilized probe hybridize or bindto the probe. After separation of, e.g., by washing off, any unboundmaterial, the bound, labeled sequences are detected and measured. Themeasurement is typically conducted with computer assistance. Using DNAarray assays, complex mixtures of labeled nucleic acids, e.g., nucleicacid fragments derived a restriction digestion of genomic DNA fromnon-cancerous tissue, can be analyzed. DNA array technologies have madeit possible to determine heterozygosity of a large number of informativeloci of interest (e.g., SNPs, RFLPs, STRs, etc.) throughout the genome.

In certain embodiments, high-density oligonucleotide arrays are used inthe methods of the invention. These arrays containing thousands ofoligonucleotides complementary to defined sequences, at definedlocations on a surface can be synthesized in situ on the surface by, forexample, photolithographic techniques (see, e.g., Fodor et al., 1991,Science 251:767-773; Pease et al., 1994, Proc. Natl. Acad. Sci. U.S.A.91:5022-5026; Lockhart et al., 1996, Nature Biotechnology 14:1675; U.S.Pat. Nos. 5,578,832; 5,556,752; 5,510,270; 5,445,934; 5,744,305; and6,040,138). Methods for generating arrays using inkjet technology for insitu oligonucleotide synthesis are also known in the art (see, e.g.,Blanchard, International Patent Publication WO 98/41531, published Sep.24, 1998; Blanchard et al., 1996, Biosensors And Bioelectronics11:687-690; Blanchard, 1998, in Synthetic DNA Arrays in GeneticEngineering, Vol. 20, J. K. Setlow, Ed., Plenum Press, New York at pages111-123). Another method for attaching the nucleic acids to a surface isby printing on glass plates, as is described generally by Schena et al.(1995, Science 270:467-470). Other methods for making microarrays, e.g.,by masking (Maskos and Southern, 1992, Nucl. Acids. Res. 20:1679-1684),may also be used. When these methods are used, oligonucleotides (e.g.,15 to 60-mers) of known sequence are synthesized directly on a surfacesuch as a derivatized glass slide. The array produced can be redundant,with several oligonucleotide molecules corresponding to each informativelocus of interest (e.g., SNPs, RFLPs, STRs, etc.).

One exemplary means for generating the oligonucleotide probes of the DNAarray is by synthesis of synthetic polynucleotides or oligonucleotides,e.g., using N-phosphonate or phosphoramidite chemistries (Froehler etal., 1986, Nucleic Acid Res. 14:5399-5407; McBride et al., 1983,Tetrahedron Lett. 24:246-248). Synthetic sequences are typically betweenabout 15 and about 600 bases in length, more typically between about 20and about 100 bases, most preferably between about 40 and about 70 basesin length. In some embodiments, synthetic nucleic acids includenon-natural bases, such as, but by no means limited to, inosine. Asnoted above, nucleic acid analogues may be used as binding sites forhybridization. An example of a suitable nucleic acid analogue is peptidenucleic acid (see, e.g., Egholm et al., 1993, Nature 363:566-568; U.S.Pat. No. 5,539,083). In alternative embodiments, the hybridization sites(i.e., the probes) are made from plasmid or phage clones of regions ofgenomic DNA corresponding to SNPs or the complement thereof. The size ofthe oligonucleotide probes used in the methods of the invention can beat least 10, 20, 25, 30, 35, 40, 45, or 50 nucleotides in length. It iswell known in the art that although hybridization is selective forcomplementary sequences, other sequences which are not perfectlycomplementary may also hybridize to a given probe at some level. Thus,multiple oligonucleotide probes with slight variations can be used, tooptimize hybridization of samples. To further optimize hybridization,hybridization stringency condition, e.g., the hybridization temperatureand the salt concentrations, may be altered by methods that are wellknown in the art.

In some embodiments, the high-density oligonucleotide arrays used in themethods of the invention comprise oligonucleotides corresponding toinformative loci of interest (e.g., SNPs, RFLPs, STRs, etc.). Theoligonucleotide probes may comprise DNA or DNA “mimics” (e.g.,derivatives and analogues) corresponding to a portion of eachinformative locus of interest (e.g., SNPs, RFLPs, STRs, etc.) in asubject's genome. The oligonucleotide probes can be modified at the basemoiety, at the sugar moiety, or at the phosphate backbone. Exemplary DNAmimics include, e.g., phosphorothioates. For each SNP locus, a pluralityof different oligonucleotides may be used that are complementary to thesequences of sample nucleic acids. For example, for a single informativelocus of interest (e.g., SNPs, RFLPs, STRs, etc.) about 2, 3, 4, 5, 6,7, 8,9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,44, 45, 46, 47, 48, 49, 50, or more different oligonucleotides can beused. Each of the oligonucleotides for a particular informative locus ofinterest may have a slight variation in perfect matches, mismatches, andflanking sequence around the SNP. In certain embodiments, the probes aregenerated such that the probes for a particular informative locus ofinterest comprise overlapping and/or successive overlapping sequenceswhich span or are tiled across a genomic region containing the targetsite, where all the probes contain the target site. By way of example,overlapping probe sequences can be tiled at steps of a predeterminedbase intervals, e. g. at steps of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 basesintervals. In certain embodiments, the assays can be performed usingarrays suitable for use with molecular inversion probe protocols such asdescribed by Wang et al. (2007) Genome Biol. 8, R246. Foroligonucleotide probes targeted at nucleic acid species of closelyresembled (i.e., homologous) sequences, “cross-hybridization” amongsimilar probes can significantly contaminate and confuse the results ofhybridization measurements. Cross-hybridization is a particularlysignificant concern in the detection of SNPs since the sequence to bedetected (i.e., the particular SNP) must be distinguished from othersequences that differ by only a single nucleotide. Cross-hybridizationcan be minimized by regulating either the hybridization stringencycondition and/or during post-hybridization washings. Highly stringentconditions allow detection of allelic variants of a nucleotide sequence,e.g., about 1 mismatch per 10-30 nucleotides. There is no singlehybridization or washing condition which is optimal for all differentnucleic acid sequences. For particular arrays of informative loci ofinterest, these conditions can be identical to those suggested by themanufacturer or can be adjusted by one of skill in the art. In preferredembodiments, the probes used in the methods of the invention areimmobilized (i.e., tiled) on a glass slide called a chip. For example, aDNA microarray can comprises a chip on which oligonucleotides (purifiedsingle-stranded DNA sequences in solution) have been robotically printedin an (approximately) rectangular array with each spot on the arraycorresponds to a single DNA sample which encodes an oligonucleotide. Insummary the process comprises, flooding the DNA microarray chip with alabeled sample under conditions suitable for hybridization to occurbetween the slide sequences and the labeled sample, then the array iswashed and dried, and the array is scanned with a laser microscope todetect hybridization. In certain embodiments there are at least 250,500, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000,10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000, 17,000, 18,000,19,000, 20,000, 21,000, 22,000, 23,000, 24,000, 25,000, 26,000, 27,000,28,000, 29,000, 30,000, 31,000, 32,000, 33,000,34,000, 35,000, 36,000,37,000, 38,000, 39,000, 40,000, 41,000, 42,000, 43,000, 44,000, 45,000,50,000, 60,000, 70,000, 80,000, 90,000, 100,000 or more or any range inbetween, of informative loci of interest for which probes appear on thearray (with match/mismatch probes for a single locus of interest orprobes tiled across a single locus of interest counting as one locus ofinterest). The maximum number of informative loci of interest beingprobed per array is determined by the size of the genome and geneticdiversity of the subjects species. DNA chips are well known in the artand can be purchased in pre-5 fabricated form with sequences specific toparticular species. In some embodiments, the Genome-Wide Human SNP Array6.0™ and/or the 50K XbaI arrays (Affymetrix, Santa Clara, Calif.) areused in the methods of the invention. In other embodiments, SNPs and/orDNA copy number can be detected and quantitated using sequencingmethods, such as “next-generation sequencing methods” as describedfurther above.

Signal Detection

In some embodiments, nucleic acid samples derived from a subject arehybridized to the binding sites of an array described herein. In certainembodiments, nucleic acid samples derived from each of the two sampletypes of a subject (i.e., cancerous and non-cancerous) are hybridized toseparate, though identical, arrays. In certain embodiments, nucleic acidsamples derived from one of the two sample types of a subject (i.e.,cancerous and non-cancerous) is hybridized to such an array, thenfollowing signal detection the chip is washed to remove the firstlabeled sample and reused to hybridize the remaining sample. In otherembodiments, the array is not reused more than once. In certainembodiments, the nucleic acid samples derived from each of the twosample types of a subject (i.e., cancerous and non-cancerous) aredifferently labeled so that they can be distinguished. When the twosamples are mixed and hybridized to the same array, the relativeintensity of signal from each sample is determined for each site on thearray, and any relative difference in abundance of an allele ofinformative loci of interest detected. Signals can be recorded and, insome embodiments, analyzed by computer. In one embodiment, the scannedimage is despeckled using a graphics program (e.g., Hijaak GraphicsSuite) and then analyzed using an image gridding program that creates aspreadsheet of the average hybridization at each wavelength at eachsite. If necessary, an experimentally determined correction for “crosstalk” (or overlap) between the channels for the two fluors may be made.For any particular hybridization site on the array, a ratio of theemission of the two fluorophores can be calculated, which may help ineliminating cross hybridization signals to more accurately determiningwhether a particular SNP locus is heterozygous or homozygous.

Labeling

In some embodiments, the nucleic acids samples, fragments thereof, orfragments thereof ligated to adaptor regions used in the methods of theinvention are detectably labeled. For example, the detectable label canbe a fluorescent label, e.g., by incorporation of nucleotide analogues.Other labels suitable for use in the present invention include, but arenot limited to, biotin, iminobiotin, antigens, cofactors, dinitrophenol,lipoic acid, olefinic compounds, detectable polypeptides, electron richmolecules, enzymes capable of generating a detectable signal by actionupon a substrate, and radioactive isotopes.

Radioactive isotopes include that can be used in conjunction with themethods of the invention, but are not limited to, 32P and 14C.Fluorescent molecules suitable for the present invention include, butare not limited to, fluorescein and its derivatives, rhodamine and itsderivatives, texas red, 5′carboxy-fluorescein (“FAM”), 2′,7′-dimethoxy-4′, 5′-dichloro-6-carboxy-fluorescein (“JOE”), N, N, N′,N′-tetramethyl-6-carboxy-rhodamine (“TAMRA”), 6-carboxy-X-rhodamine(“ROX”), HEX, TET, IRD40, and IRD41.

Fluorescent molecules which are suitable for use according to theinvention further include: cyamine dyes, including but not limited toCy2, Cy3, Cy3.5, CY5, Cy5.5, Cy7 and FLUORX; BODIPY dyes including butnot limited to BODIPY-FL, BODIPY-TR, BODIPY-TMR, BODIPY-630/650, andBODIPY-650/670; and ALEXA dyes, including but not limited to ALEXA-488,ALEXA-532, ALEXA-546, ALEXA-568, and ALEXA-594; as well as otherfluorescent dyes which will be known to those who are skilled in theart. Electron rich indicator molecules suitable for the presentinvention include, but are not limited to, ferritin, hemocyanin, andcolloidal gold.

Two-color fluorescence labeling and detection schemes may also be used(Shena et al., 1995, Science 270:467-470). Use of two or more labels canbe useful in detecting variations due to minor differences inexperimental conditions (e.g., hybridization conditions). In someembodiments of the invention, at least 5, 10, 20, or 100 dyes ofdifferent colors can be used for labeling. Such labeling would alsopermit analysis of multiple samples simultaneously which is encompassedby the invention.

The labeled nucleic acid samples, fragments thereof, or fragmentsthereof ligated to adaptor regions that can be used in the methods ofthe invention are contacted to a plurality of oligonucleotide probesunder conditions that allow sample nucleic acids having sequencescomplementary to the probes to hybridize thereto. Depending on the typeof label used, the hybridization signals can be detected using methodswell known to those of skill in the art including, but not limited to,X-Ray film, phosphor imager, or CCD camera. When fluorescently labeledprobes are used, the fluorescence emissions at each site of a transcriptarray can be, preferably, detected by scanning confocal lasermicroscopy. In one embodiment, a separate scan, using the appropriateexcitation line, is carried out for each of the two fluorophores used.Alternatively, a laser can be used that allows simultaneous specimenillumination at wavelengths specific to the two fluorophores andemissions from the two fluorophores can be analyzed simultaneously (seeShalon et al. (1996) Genome Res. 6, 639-645). In a preferred embodiment,the arrays are scanned with a laser fluorescence scanner with a computercontrolled X-Y stage and a microscope objective. Sequential excitationof the two fluorophores is achieved with a multi-line, mixed gas laser,and the emitted light is split by wavelength and detected with twophotomultiplier tubes. Such fluorescence laser scanning devices aredescribed, e.g., in Schena et al. (1996) Genome Res. 6, 639-645.Alternatively, a fiber-optic bundle can be used such as that describedby Ferguson et al. (1996) Nat. Biotech. 14, 1681-1684. The resultingsignals can then be analyzed to determine the presence or absence ofheterozygosity or homozygosity for informative loci of interest (e.g.,SNPs, RFLPs, STRs, etc.) using computer software.

Algorithms for Analyzing Informative Loci of Interest

Once the hybridization signal has been detected the resulting data canbe analyzed using algorithms. In certain embodiments, the algorithm fordetermining heterozygosity at informative loci of interest (e.g., SNPs,RFLPs, STRs, etc.) is based on well known methods for calling allelicimbalance (AI), loss of heterozygosity (LOH), copy number aberrations(CNA), copy number gain (CNG), and copy number decrease (CND). Forexample, AI can be determined using major copy proportion (MCP) whereinAI for a given SNP is called, when the MCP value is greater than 0.60,0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.69, 0.70, 0.71, 0.72,0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.80. 0.81, 0.82, 0.83, 0.84,0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.92, 0.93, 0.94, 0.95,0.96, 0.97, 0.98, or 0.99. Once calling is determined, enumerationmethods can further be applied. For example, GCAS can be determined, forexample, by: 1) the count of the total number of SNPs affected by AI orcopy gain or LOH, 2) the count of the number of regions affected by AI(e.g., NAI as described further in the Examples; a single region isdefined as a string of neighboring SNPs all showing AI bounded on atleast one side by SNPs showing no AI/retention of heterozygosity. Theregion size is defined by the length of the chromosome represented bythe string of SNPs with AI); 3) the count of the number of chromosomeswith whole chromosome loss, or 4) the count of the number of chromosomalregions with CNA, CNG, CND, etc. Additional representative illustrationsof such well known algorithms are provided in the Examples sectionbelow.

Computer Implementation Systems and Methods

In certain embodiments, the methods of the invention implement acomputer program to calculate a chromosomal aberration score (e.g.,GCAS, telomeric aberration score, telomeric allelic imbalance score,etc.). For example, a computer program can be used to perform thealgorithms described herein. A computer system can also store andmanipulate data generated by the methods of the present invention whichcomprises a plurality of hybridization signal changes/profiles duringapproach to equilibrium in different hybridization measurements andwhich can be used by a computer system in implementing the methods ofthis invention. In certain embodiments, a computer system receives probehybridization data; (ii) stores probe hybridization data; and (iii)compares probe hybridization data to determine the state of informativeloci of interest in said nucleic acid sample from cancerous orpre-cancerous tissue. The GCAS is then calculated. In some embodiments,a computer system (i) compares the determined GCAS to a threshold value;and (ii) outputs an indication of whether said GCAS is above or below athreshold value, or a phenotype based on said indication. In certainembodiments, such computer systems are also considered part of thepresent invention.

Numerous types of computer systems can be used to implement the analyticmethods of this invention according to knowledge possessed by a skilledartisan in the bioinformatics and/or computer arts.

Several software components can be loaded into memory during operationof such a computer system. The software components can comprise bothsoftware components that are standard in the art and components that arespecial to the present invention (e.g., dCHIP software described in Linet al. (2004) Bioinformatics 20, 1233-1240; CRLMM software described inSilver et al. (2007) Cell 128, 991-1002; Aroma Affymetrix softwaredescribed in Richardson et al. (2006) Cancer Cell 9, 121-132. Themethods of the invention can also be programmed or modeled inmathematical software packages that allow symbolic entry of equationsand high-level specification of processing, including specificalgorithms to be used, thereby freeing a user of the need toprocedurally program individual equations and algorithms. Such packagesinclude, e.g., Matlab from Mathworks (Natick, Mass.), Mathematica fromWolfram Research (Champaign, Ill.) or S-Plus from MathSoft (Seattle,Wash.). In certain embodiments, the computer comprises a database forstorage of hybridization signal profiles. Such stored profiles can beaccessed and used to calculate GCAS. For example, of the hybridizationsignal profile of a sample derived from the non-cancerous tissue of asubject and/or profiles generated from population-based distributions ofinformative loci of interest in relevant populations of the same specieswere stored, it could then be compared to the hybridization signalprofile of a sample derived from the cancerous tissue of the subject.

In addition to the exemplary program structures and computer systemsdescribed herein, other, alternative program structures and computersystems will be readily apparent to the skilled artisan. Suchalternative systems, which do not depart from the above describedcomputer system and programs structures either in spirit or in scope,are therefore intended to be comprehended within the accompanyingclaims.

Once a laboratory technician or laboratory professional or group oflaboratory technicians or laboratory professionals determines whether asample has a chromosomal aberration at a plurality of assay loci asdescribed above (e.g., step (1) in many of the methods above), the sameor a different laboratory technician or laboratory professional (orgroup) can analyze a plurality of test loci to determine whether theyhave a chromosomal aberration (e.g., step (2) in many of the methodsabove). Next, the same or a different laboratory technician orlaboratory professional (or group) can combine the chromosomalaberration data from the test loci to derive a chromosomal aberrationscore (e.g., step (3) in many of the methods above). Optionally, thesame or a different laboratory technician or laboratory professional (orgroup) can correlate a high chromosomal aberration score to an increasedlikelihood of response to a particular therapy (e.g., those mentionedabove). For example, one or more laboratory technicians or laboratoryprofessionals can identify a patient having cancer cells that weredetected to have a high chromosomal aberration score by associating thathigh chromosomal aberration score or the result (or results or a summaryof results) of the performed diagnostic analysis with the correspondingpatient's name, medical record, symbolic/numerical identifier, or acombination thereof. Such identification can be based solely ondetecting the presence of a high chromosomal aberration score or can bebased at least in part on detecting the presence of a high chromosomalaberration score. For example, a laboratory technician or laboratoryprofessional can identify a patient having cancer cells that weredetected to have a high chromosomal aberration score as having cancercells with an increased likelihood of response to a particular therapybased on a combination of a high chromosomal aberration score and theresults of other genetic and biochemical tests performed at the testinglaboratory.

FIG. 23 shows an exemplary process by which a computing system candetermine a chromosomal aberration score. The process begins at box 300,where data regarding the genotype (e.g., relative or absolute copynumber, homozygous, heterozygous) of a plurality of loci along achromosome is collected by the computing system. As described herein,any appropriate assay such as a SNP array-based assay orsequencing-based assay can be used to assess loci along a chromosome forgenotype. In some cases, a system including a signal detector and acomputer can be used to collect data (e.g., fluorescent signals orsequencing results) regarding the genotype of the plurality of loci. Atbox 310, data regarding the genotype of a plurality of loci as well asthe location or spatial relationship of each locus is assessed by thecomputing system to determine, e.g., the length of any chromosomalaberration (e.g., allelic imbalance) regions present along a chromosomeor the number of telomeric aberration (e.g., allelic imbalance) regions.At box 320, data regarding the number of chromosomal aberration regionsdetected and optionally the length or the location of each detectedchromosomal aberration region is assessed by the computing system todetermine the number of chromosomal aberration regions that aretelomeric regions. At box 330, the computing system formats an outputproviding an indication of the presence or absence of a high chromosomalaberration score. Once formatted, the computing system can present theoutput to a user (e.g., a laboratory technician, clinician, or medicalprofessional). As described herein, the presence or absence of a highchromosomal aberration score can be used to provide an indication aboutpossible cancer treatment regimens.

FIG. 24 is a diagram of an example of a computer device 1400 and amobile computer device 1450, which may be used with the techniquesdescribed herein. Computing device 1400 is intended to represent variousforms of digital computers, such as laptops, desktops, workstations,personal digital assistants, servers, blade servers, mainframes, andother appropriate computers. Computing device 1450 is intended torepresent various forms of mobile devices, such as personal digitalassistants, cellular telephones, smart phones, and other similarcomputing devices. The components shown here, their connections andrelationships, and their functions, are meant to be exemplary only, andare not meant to limit implementations of the inventions describedand/or claimed in this document.

Computing device 1400 includes a processor 1402, memory 1404, a storagedevice 1406, a high-speed interface 1408 connecting to memory 1404 andhigh-speed expansion ports 1410, and a low speed interface 1415connecting to low speed bus 1414 and storage device 1406. Each of thecomponents 1402, 1404, 1406, 1408, 1410, and 1415, are interconnectedusing various busses, and may be mounted on a common motherboard or inother manners as appropriate. The processor 1402 can processinstructions for execution within the computing device 1400, includinginstructions stored in the memory 1404 or on the storage device 1406 todisplay graphical information for a GUI on an external input/outputdevice, such as display 1416 coupled to high speed interface 1408. Inother implementations, multiple processors and/or multiple buses may beused, as appropriate, along with multiple memories and types of memory.Also, multiple computing devices 1400 may be connected, with each deviceproviding portions of the necessary operations (e.g., as a server bank,a group of blade servers, or a multi-processor system).

The memory 1404 stores information within the computing device 1400. Inone implementation, the memory 1404 is a volatile memory unit or units.In another implementation, the memory 1404 is a non-volatile memory unitor units. The memory 1404 may also be another form of computer-readablemedium, such as a magnetic or optical disk.

The storage device 1406 is capable of providing mass storage for thecomputing device 1400. In one implementation, the storage device 1406may be or contain a computer-readable medium, such as a floppy diskdevice, a hard disk device, an optical disk device, or a tape device, aflash memory or other similar solid state memory device, or an array ofdevices, including devices in a storage area network or otherconfigurations. A computer program product can be tangibly embodied inan information carrier. The computer program product may also containinstructions that, when executed, perform one or more methods, such asthose described herein. The information carrier is a computer- ormachine-readable medium, such as the memory 1404, the storage device1406, memory on processor 1402, or a propagated signal.

The high speed controller 1408 manages bandwidth-intensive operationsfor the computing device 1400, while the low speed controller 1415manages lower bandwidth-intensive operations. Such allocation offunctions is exemplary only. In one implementation, the high-speedcontroller 1408 is coupled to memory 1404, display 1416 (e.g., through agraphics processor or accelerator), and to high-speed expansion ports1410, which may accept various expansion cards (not shown). In theimplementation, low-speed controller 1415 is coupled to storage device1406 and low-speed expansion port 1414. The low-speed expansion port,which may include various communication ports (e.g., USB, Bluetooth,Ethernet, or wireless Ethernet) may be coupled to one or moreinput/output devices, such as a keyboard, a pointing device, a scanner,an optical reader, a fluorescent signal detector, or a networking devicesuch as a switch or router, e.g., through a network adapter.

The computing device 1400 may be implemented in a number of differentforms, as shown in the figure. For example, it may be implemented as astandard server 1420, or multiple times in a group of such servers. Itmay also be implemented as part of a rack server system 1424. Inaddition, it may be implemented in a personal computer such as a laptopcomputer 1422. Alternatively, components from computing device 1400 maybe combined with other components in a mobile device (not shown), suchas device 1450. Each of such devices may contain one or more ofcomputing device 1400, 1450, and an entire system may be made up ofmultiple computing devices 1400, 1450 communicating with each other.

Computing device 1450 includes a processor 1452, memory 1464, aninput/output device such as a display 1454, a communication interface1466, and a transceiver 1468, among other components (e.g., a scanner,an optical reader, a fluorescent signal detector). The device 1450 mayalso be provided with a storage device, such as a microdrive or otherdevice, to provide additional storage. Each of the components 1450,1452, 1464, 1454, 1466, and 1468, are interconnected using variousbuses, and several of the components may be mounted on a commonmotherboard or in other manners as appropriate.

The processor 1452 can execute instructions within the computing device1450, including instructions stored in the memory 1464. The processormay be implemented as a chipset of chips that include separate andmultiple analog and digital processors. The processor may provide, forexample, for coordination of the other components of the device 1450,such as control of user interfaces, applications run by device 1450, andwireless communication by device 1450.

Processor 1452 may communicate with a user through control interface1458 and display interface 1456 coupled to a display 1454. The display1454 may be, for example, a TFT LCD (Thin-Film-Transistor Liquid CrystalDisplay) or an OLED (Organic Light Emitting Diode) display, or otherappropriate display technology. The display interface 1456 may compriseappropriate circuitry for driving the display 1454 to present graphicaland other information to a user. The control interface 1458 may receivecommands from a user and convert them for submission to the processor1452. In addition, an external interface 1462 may be provide incommunication with processor 1452, so as to enable near areacommunication of device 1450 with other devices. External interface 1462may provide, for example, for wired communication in someimplementations, or for wireless communication in other implementations,and multiple interfaces may also be used.

The memory 1464 stores information within the computing device 1450. Thememory 1464 can be implemented as one or more of a computer-readablemedium or media, a volatile memory unit or units, or a non-volatilememory unit or units. Expansion memory 1474 may also be provided andconnected to device 1450 through expansion interface 1472, which mayinclude, for example, a SIMM (Single In Line Memory Module) cardinterface. Such expansion memory 1474 may provide extra storage spacefor device 1450, or may also store applications or other information fordevice 1450. For example, expansion memory 1474 may include instructionsto carry out or supplement the processes described herein, and mayinclude secure information also. Thus, for example, expansion memory1474 may be provide as a security module for device 1450, and may beprogrammed with instructions that permit secure use of device 1450. Inaddition, secure applications may be provided via the SIMM cards, alongwith additional information, such as placing identifying information onthe SIMM card in a non-hackable manner.

The memory may include, for example, flash memory and/or NVRAM memory,as discussed below. In one implementation, a computer program product istangibly embodied in an information carrier. The computer programproduct contains instructions that, when executed, perform one or moremethods, such as those described herein. The information carrier is acomputer- or machine-readable medium, such as the memory 1464, expansionmemory 1474, memory on processor 1452, or a propagated signal that maybe received, for example, over transceiver 1468 or external interface1462.

Device 1450 may communicate wirelessly through communication interface1466, which may include digital signal processing circuitry wherenecessary. Communication interface 1466 may provide for communicationsunder various modes or protocols, such as GSM voice calls, SMS, EMS, orMMS messaging, CDMA, TDMA, PDC, WCDMA, CDMA2000, or GPRS, among others.Such communication may occur, for example, through radio-frequencytransceiver 1468. In addition, short-range communication may occur, suchas using a Bluetooth, WiFi, or other such transceiver (not shown). Inaddition, GPS (Global Positioning System) receiver module 1470 mayprovide additional navigation- and location-related wireless data todevice 1450, which may be used as appropriate by applications running ondevice 1450.

Device 1450 may also communicate audibly using audio codec 1460, whichmay receive spoken information from a user and convert it to usabledigital information. Audio codec 1460 may likewise generate audiblesound for a user, such as through a speaker, e.g., in a handset ofdevice 1450. Such sound may include sound from voice telephone calls,may include recorded sound (e.g., voice messages, music files, etc.) andmay also include sound generated by applications operating on device1450.

The computing device 1450 may be implemented in a number of differentforms, as shown in the figure. For example, it may be implemented as acellular telephone 1480. It may also be implemented as part of asmartphone 1482, personal digital assistant, or other similar mobiledevice.

Various implementations of the systems and techniques described hereincan be realized in digital electronic circuitry, integrated circuitry,specially designed ASICs (application specific integrated circuits),computer hardware, firmware, software, and/or combinations thereof.These various implementations can include implementation in one or morecomputer programs that are executable and/or interpretable on aprogrammable system including at least one programmable processor, whichmay be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor, and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms “machine-readable medium” and“computer-readable medium” refer to any computer program product,apparatus and/or device (e.g., magnetic discs, optical disks, memory,and Programmable Logic Devices (PLDs)) used to provide machineinstructions and/or data to a programmable processor, including amachine-readable medium that receives machine instructions as amachine-readable signal. The term “machine-readable signal” refers toany signal used to provide machine instructions and/or data to aprogrammable processor.

To provide for interaction with a user, the systems and techniquesdescribed herein can be implemented on a computer having a displaydevice (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display)monitor) for displaying information to the user and a keyboard and apointing device (e.g., a mouse or a trackball) by which the user canprovide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well; for example, feedbackprovided to the user can be any form of sensory feedback (e.g., visualfeedback, auditory feedback, or tactile feedback); and input from theuser can be received in any form, including acoustic, speech, or tactileinput.

The systems and techniques described herein can be implemented in acomputing system that includes a back end component (e.g., as a dataserver), or that includes a middleware component (e.g., an applicationserver), or that includes a front end component (e.g., a client computerhaving a graphical user interface or a Web browser through which a usercan interact with an implementation of the systems and techniquesdescribed herein), or any combination of such back end, middleware, orfront end components. The components of the system can be interconnectedby any form or medium of digital data communication (e.g., acommunication network). Examples of communication networks include alocal area network (“LAN”), a wide area network (“WAN”), and theInternet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

The results of any analyses according to the invention will often becommunicated to physicians, genetic counselors and/or patients (or otherinterested parties such as researchers) in a transmittable form that canbe communicated or transmitted to any of the above parties. Such a formcan vary and can be tangible or intangible. The results can be embodiedin descriptive statements, diagrams, photographs, charts, images or anyother visual forms. For example, graphs or diagrams showing genotype orLOH (or HRD status) information can be used in explaining the results.The statements and visual forms can be recorded on a tangible mediumsuch as papers, computer readable media such as floppy disks, compactdisks, flash memory, etc., or in an intangible medium, e.g., anelectronic medium in the form of email or website on internet orintranet. In addition, results can also be recorded in a sound form andtransmitted through any suitable medium, e.g., analog or digital cablelines, fiber optic cables, etc., via telephone, facsimile, wirelessmobile phone, internet phone and the like.

Thus, the information and data on a test result can be produced anywherein the world and transmitted to a different location. As an illustrativeexample, when an assay is conducted outside the United States, theinformation and data on a test result may be generated, cast in atransmittable form as described above, and then imported into the UnitedStates. Accordingly, the present invention also encompasses a method forproducing a transmittable form of information on an LOH signature for atleast one patient sample. The method comprises the steps of (1)determining an LOH signature according to methods of the presentinvention; and (2) embodying the result of the determining step in atransmittable form. The transmittable form is a product of such amethod.

In some cases, a computing system provided herein can be configured toinclude one or more sample analyzers. A sample analyzer can beconfigured to produce a plurality of signals about genomic DNA of atleast one pair of human chromosomes of a cancer cell. For example, asample analyzer can produce signals that are capable of beinginterpreted in a manner that identifies the homozygous or heterozygousnature of loci along a chromosome. In some cases, a sample analyzer canbe configured to carry out one or more steps of a SNP array-based assayor sequencing-based assay and can be configured to produce and/orcapture signals from such assays. In some cases, a computing systemprovided herein can be configured to include a computing device. In suchcases, the computing device can be configured to receive signals from asample analyzer. The computing device can include computer-executableinstructions or a computer program (e.g., software) containingcomputer-executable instructions for carrying out one or more of themethods or steps described herein. In some cases, suchcomputer-executable instructions can instruct a computing device toanalyze signals from a sample analyzer, from another computing device,from a SNP array-based assay, or from a sequencing-based assay. Theanalysis of such signals can be carried out to determine genotypes,chromosomal aberration at certain loci, regions of chromosomalaberration, the number of chromosomal aberration regions, to determinethe location of chromosomal aberration regions (e.g., telomeric), todetermine the number of chromosomal aberration regions having aparticular location (e.g., telomeric), to determine whether or not asample is positive for a high chromosomal aberration score, to determinea likelihood that a cancer patient will respond to a particular cancertreatment regimen (e.g., a regimen as described above), or to determinea combination of these items.

In some cases, a computing system provided herein can includecomputer-executable instructions or a computer program (e.g., software)containing computer-executable instructions for formatting an outputproviding an indication about the number of chromosomal aberrationregions, the location of chromosomal aberration regions (e.g.,telomeric), the number of LOH regions having a particular location(e.g., telomeric), whether or not a sample is positive for a highchromosomal aberration score, a likelihood that a cancer patient willrespond to a particular cancer treatment regimen (e.g., a regimen asdescribed above), or a combination of these items. In some cases, acomputing system provided herein can include computer-executableinstructions or a computer program (e.g., software) containingcomputer-executable instructions for determining a desired cancertreatment regimen for a particular patient based at least in part on thepresence or absence of a high chromosomal aberration score.

In some cases, a computing system provided herein can include apre-processing device configured to process a sample (e.g., cancercells) such that a SNP array-based assay or sequencing-based assay canbe performed. Examples of pre-processing devices include, withoutlimitation, devices configured to enrich cell populations for cancercells as opposed to non-cancer cells, devices configured to lyse cellsand/or extract genomic nucleic acid, and devices configured to enrich asample for particular genomic DNA fragments.

In general, one aspect of this invention features a method for assessingLOH in a cancer cell or genomic DNA thereof. In some embodiments, themethod comprises, or consists essentially of, (a) detecting, in a cancercell or genomic DNA derived therefrom, LOH regions in at least one pairof human chromosomes of the cancer cell (e.g., any pair of humanchromosomes other than a human X/Y sex chromosome pair); and (b)determining the number and size (e.g., length) of said LOH regions. Insome embodiments, LOH regions are analyzed in a number of chromosomepairs that are representative of the entire genome (e.g., enoughchromosomes are analyzed such that the number and size of LOH regionsare expected to be representative of the number and size of LOH regionsacross the genome). In some embodiments, the method further comprisesdetermining the total number of LOH regions that are longer than about1.5, 5, 12, 13, 14, 15, 16, 17 or more (preferably 14, 15, 16 or more,more preferably 15 or more) megabases but shorter than the entire lengthof the respective chromosome which the LOH region is located within(Indicator LOH Regions). Alternatively or additionally, the totalcombined length of such Indicator LOH Regions is determined. In somespecific embodiments, if that total number of Indicator LOH Regions ortotal combined length of Indicator LOH Regions is equal to or greaterthan a predetermined reference number, then said cancer cell or genomicDNA or a patient having said cancer cell or genomic DNA is identified ashaving an HDR-deficiency LOH signature.

Other embodiments of the present invention are described in thefollowing Examples. The present invention is further illustrated by thefollowing examples which should not be construed as further limiting.

The following paragraphs define the invention in more detail

1. An assay for selecting therapy for a subject having cancer, the assaycomprising

subjecting a biological sample comprising a cancer cell or nucleic acidfrom a cancer cell taken from the subject to telomeric allelic imbalance(tAI) analysis;

detecting the number of telomeric allelic imbalance (NtAI) in the cancercell or nucleic acid from the cancer cell, and

selecting a platinum-comprising therapy for the subject when the NtAI isdetected to be above a reference value based on the recognition thatplatinum-comprising therapy is effective in patients who have NtAI abovethe reference value; and selecting a non-platinum-comprising cancertherapy for the subject when the NtAI is detected to be below areference value based on the recognition that platinum-comprising cancertherapy is not effective in patients who have the NtAI below a referencevalue.

2. The assay of paragraph 1 further comprising the step of treating thesubject with the selected therapy.

3. The assay of any of the preceding paragraphs, wherein the cancer isbreast cancer or ovarian cancer.

4. The assay of any of the preceding paragraphs, wherein the referencevalue is 22.

5. The assay of any of the preceding paragraphs, wherein the referencevalue is 24.

6. The assay of any of the preceding paragraphs, wherein the referencevalue is 27.

7. The assay of any of the preceding paragraphs, wherein the cancer celldoes not have mutations in the BRCA1 and/or BRCA2 gene.

8. The assay of any of the preceding paragraphs further comprising astep of assaying for BRCA1 mRNA expression or methylation status of theBRCA1 promoter, detecting the amount of BRCA1 mRNA expression or theamount of methylation of the BRCA1 promoter, wherein the platinumcomprising therapy is selected when decreased expression of BRCA1 orincreased methylation of BRCA1 promoter is detected.

9. A method for selecting platinum-comprising therapy for a subjecthaving cancer comprising

subjecting a biological sample taken from the subject to allelicimbalance (AI) analysis;

detecting the number of AI; and

selecting platinum-comprising cancer therapy for the subject when thenumber of AIs is above a reference value based on the recognition thatplatinum-comprising cancer therapy is effective in patients who have thenumber of AIs is above a reference value.

10. The method of any of the preceding paragraphs further comprising thestep of treating the subject with platinum-comprising cancer therapywhen platinum-comprising cancer therapy is selected.

11. The method of any of the preceding paragraphs, wherein the cancer isselected from breast cancer and ovarian cancer.

12. The method of any of the preceding paragraphs, wherein the breastcancer does not have a BRCA1 mutations.

13. The method of any of the preceding paragraphs, wherein the allelicimbalance is within about 25 kB of a copy number variation (CNV).

14. The method of any of the preceding paragraphs, wherein the CNV ispericentromeric or subtelomeric CNV.

15. The method of any of the preceding paragraphs, wherein the allelicimbalance is telomeric allelic imbalance.

16. A method comprising:

detecting, in a cancer cell or genomic DNA derived therefrom, allelicimbalance in a representative number of pairs of human chromosomes ofthe cancer cell; and

determining the number of allelic imbalance.

17. The method of Paragraph 16, said representative number of pairs ofhuman chromosomes is representative of the entire genome.

18. The method of Paragraph 16-17, further comprising correlating anincreased number of allelic imbalance regions to an increased likelihoodof deficiency in HDR.

19. The method of paragraph 16-18, further comprising correlating anincreased number of allelic imbalance regions to an increased likelihoodof said cancer cell to respond to platinum comprising cancer therapy.

20. The method of paragraph 16-19, further comprising correlating anon-increased number of allelic imbalance regions to a decreasedlikelihood of said cancer cell to respond to platinum comprising cancertherapy.

21. The method of paragraph 16-21, wherein the platinum comprisingcancer therapy comprises cisplatin, carboplatin, oxalaplatin, orpicoplatin.

22. A method comprising:

a) detecting, in a cancer cell or genomic DNA derived therefrom, LOHregions in a representative number of pairs of human chromosomes of thecancer cell; and

b) determining the number and size of said LOH regions.

23. The method of Paragraph 22, said representative number of pairs ofhuman chromosomes is representative of the entire genome.

24. The method of Paragraph 22-23, further comprising correlating anincreased number of LOH regions of a particular size to an increasedlikelihood of deficiency in HDR.

25. The method of Paragraph 22-24, wherein said particular size islonger than about 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 75, or 100 megabases andless than the length of the entire chromosome that contains the LOHregion.

26. The method of any of the paragraphs 22-25, wherein 6, 7, 8, 9, 10,11, 12 or 13 or more LOH regions of said particular size are correlatedto an increased likelihood of deficiency in HDR.

27. A method of determining prognosis in a patient comprising:

a) determining whether the patient comprises cancer cells having an LOHsignature, wherein the presence of more than a reference number of LOHregions in at least one pair of human chromosomes of a cancer cell ofthe cancer patient that are longer than a first length but shorter thanthe length of the whole chromosome containing the LOH region indicatesthat the cancer cells have the LOH signature, wherein the at least onepair of human chromosomes is not a human X/Y sex chromosome pair,wherein the first length is about 1.5 or more megabases, an

b) (1) determining, based at least in part on the presence of the LOHsignature, that the patient has a relatively good prognosis, or b)(2)determining, based at least in part on the absence of the LOH signature,that the patient has a relatively poor prognosis

28. A composition comprising a therapeutic agent selected from the groupconsisting of DNA damaging agent, anthracycline, topoisomerase Iinhibitor, and PARP inhibitor for use in treating a cancer selected fromthe group consisting of breast cancer, ovarian cancer, liver cancer,esophageal cancer, lung cancer, head and neck cancer, prostate cancer,colon cancer, rectal cancer, colorectal cancer, and pancreatic cancer ina patient with more than a reference number of LOH regions in at leastone pair of human chromosomes of a cancer cell of the patient that arelonger than a first length but shorter than the length of the wholechromosome containing the LOH region, wherein the at least one pair ofhuman chromosomes is not a human X/Y sex chromosome pair, wherein thefirst length is about 1.5 or more megabases.

29. The composition of any of the preceding Paragraphs, wherein said LOHregions are determined in at least two, five, ten or 21 pairs of humanchromosomes.

30. The composition of any of the preceding paragraphs, wherein thetotal number of said LOH regions is 9, 15, 20 or more.

31. The composition of any of the preceding paragraphs, wherein saidfirst length is about 6, 12, or 15 or more megabases.

32. The composition of any of the preceding paragraphs, wherein saidreference number is 6, 7, 8, 9, 10, 11, 12 or 13 or greater.

33. A method of treating cancer in a patient, comprising:

a) determining in a sample from said patient the number of LOH regionsin at least one pair of human chromosomes of a cancer cell of the cancerpatient that are longer than a first length but shorter than the lengthof the whole chromosome containing the LOH region indicates that thecancer cells have the LOH signature, wherein the at least one pair ofhuman chromosomes is not a human X/Y sex chromosome pair, wherein thefirst length is about 1.5 or more megabases;

b) providing a test value derived from the number of said LOH regions;

c) comparing said test value to one or more reference values derivedfrom the number of said LOH regions in a reference population (e.g.,mean, median, terciles, quartiles, quintiles, etc.); and

d) administering to said patient an anti-cancer drug, or recommending orprescribing or initiating a treatment regimen comprising chemotherapyand/or a synthetic lethality agent based at least in part on saidcomparing step revealing that the test value is greater (e.g., at least2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater; at least 1, 2, 3, 4,5, 6, 7, 8, 9, or 10 standard deviations greater) than at least one saidreference value; or

e) recommending or prescribing or initiating a treatment regimen notcomprising chemotherapy and/or a synthetic lethality agent based atleast in part on said comparing step revealing that the test value isnot greater (e.g., not more than 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or10-fold greater; not more than 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standarddeviations greater) than at least one said reference value.

34. The method of Paragraph 33, wherein said LOH regions are determinedin at least two, five, ten or 21 pairs of human chromosomes.

35. The method of Paragraph 33-34, wherein the total number of said LOHregions is 9, 15, 20 or more.

36. The method of Paragraph 33-35, wherein said first length is about 6,12, or 15 or more megabases.

37. The method of Paragraph 33-36, wherein said reference number is 6,7, 8, 9, 10, 11, 12 or 13 or greater.

38. The method of Paragraph 33-37, wherein said chemotherapy is selectedfrom the group consisting of a DNA damaging agent, an anthracycline, anda topoisomerase I inhibitor and/or wherein said synthetic lethalityagent is a PARP inhibitor drug.

39. The method of Paragraph 33-38, wherein said DNA damaging agent iscisplatin, carboplatin, oxalaplatin, or picoplatin, said anthracyclineis epirubincin or doxorubicin, said topoisomerase I inhibitor iscampothecin, topotecan, or irinotecan, and/or said PARP inhibitor isiniparib, olaparib or velapirib.

40. A composition comprising a therapeutic agent selected from the groupconsisting of platinum comprising cancer therapy and anthracycline foruse in treating a cancer selected from the group consisting of breastcancer, ovarian cancer, liver cancer, esophageal cancer, lung cancer,head and neck cancer, prostate cancer, colon cancer, rectal cancer,colorectal cancer, and pancreatic cancer in a patient with increasedallelic imbalance.

41. The composition of paragraph 40, wherein the allelic imbalance istelomeric allelic imbalance.

42. The composition of paragraph 40-41, wherein the allelic imbalance iswithin about 25 kB of a copy number variation (CNV).

43. The composition of paragraph 40-42, wherein the patient is furtherdetermined not to carry a BRCA1 and/or BRCA2 mutation.

44. The composition of paragraph 40-43, wherein the patient is furtherdetermined to have decreased BRCA1 mRNA amount in the cancer cell and/oris further determined to have increased methylation of the BRCA1promoter region.

45. A method for predicting the outcome of anti-cancer treatment of asubject with a cell hyperproliferative disorder, comprising determininga global chromosomal aberration score (GCAS), comprising obtaining abiological sample from the subject and determining whether a pluralityof chromosomal regions displaying a chromosomal aberration exists withina plurality of chromosomal loci, wherein said chromosomal aberrationsare selected from the group consisting of allelic imbalance (NAI), lossof heterozygosity (NLOH), copy number aberrations (NCNA), copy numbergain (NCNG), copy number decrease (NCND) and combinations thereof,relative to a control, and wherein the presence of a plurality ofchromosomal regions displaying said chromosomal aberrations predicts theoutcome of anti-cancer treatment of the subject.

46. The method of paragraph 45, wherein the anti-cancer treatment ischemotherapy treatment.

47. The method of paragraph 45-46, wherein the chemotherapy treatmentcomprises platinum-based chemotherapeutic agents.

48. The method of paragraph 45-47, wherein the platinum-basedchemotherapeutic agents are selected from the group consisting ofcisplatin, carboplatin, oxaliplatin, nedaplatin, and iproplatin.

49. The method of paragraph 45-48, wherein the subject is a human.

50. The method of paragraph 45-49, wherein the cell hyperproliferativedisorder is selected from the group consisting of breast cancer, ovariancancer, transitional cell bladder cancer, bronchogenic lung cancer,thyroid cancer, pancreatic cancer, prostate cancer, uterine cancer,testicular cancer, gastric cancer, soft tissue and osteogenic sarcomas,neuroblastoma, Wilms' tumor, malignant lymphoma (Hodgkin's andnon-Hodgkin's), acute myeloblastic leukemia, acute lymphoblasticleukemia, Kaposi's sarcoma, Ewing's tumor, refractory multiple myeloma,and squamous cell carcinomas of the head, neck, cervix, colon cancer,melanoma, and vagina.

51. The method of paragraph 45-50, wherein the biological sample isselected from the group consisting of cells, cell lines, histologicalslides, frozen core biopsies, paraffin embedded tissues, formalin fixedtissues, biopsies, whole blood, nipple aspirate, serum, plasma, buccalscrape, saliva, cerebrospinal fluid, urine, stool, and bone marrow.

52. The method of paragraph 45-51, wherein the biological sample isenriched for the presence of hyperproliferative cells to at least 75% ofthe total population of cells.

53. The method of paragraph 45-52, wherein the enrichment is performedaccording to at least one technique selected from the group consistingof needle microdissection, laser microdissection, fluorescence activatedcell sorting, and immunological cell sorting.

54. The method of paragraph 45-53, wherein an automated machine performsthe at least one technique to thereby transform the biological sampleinto a purified form enriched for the presence of hyperproliferativecells.

55. The method of paragraph 45-54, wherein the biological sample isobtained before the subject has received adjuvant chemotherapy.

56. The method of paragraph 45-55, wherein the biological sample isobtained after the subject has received adjuvant chemotherapy.

57. The method of paragraph 45-56, wherein the control is determinedfrom a non-cell hyperproliferative cell sample from the patient ormember of the same species to which the patient belongs.

58. The method of paragraph 45-58, wherein the control is determinedfrom the average frequency of genomic locus appearance of chromosomalregions of the same ethnic group within the species to which the patientbelongs.

59. The method of paragraph 45-58, wherein the control is fromnon-cancerous tissue that is the same tissue type as said canceroustissue of the subject.

60. The method of paragraph 45-59, wherein the control is fromnon-cancerous tissue that is not the same tissue type as said canceroustissue of the subject.

61. The method of paragraph 45-60, wherein NAI is determined using majorcopy proportion (MCP).

62. The method of paragraph 45-61, wherein NAI for a given genomicregion is counted when MCP is greater than 0.70.

63. The method of paragraph 45-62, wherein the plurality of chromosomalloci are randomly distributed throughout the genome at least every 100Kb of DNA.

64. The method of paragraph 45-63, wherein the plurality of chromosomalloci comprise at least one chromosomal locus on each of the 23 humanchromosome pairs.

65. The method of paragraph 45-64, wherein the plurality of chromosomalloci comprise at least one chromosomal locus on each arm of each of the23 human chromosome pairs.

66. The method of paragraph 45-65, wherein the plurality of chromosomalloci comprise at least one chromosomal locus on at least one telomere ofeach of the 23 human chromosome pairs.

67. The method of paragraph 45-66, wherein the plurality of chromosomalloci comprise at least one chromosomal locus on each telomere of each ofthe 23 human chromosome pairs.

68. The method of paragraph 45-67, wherein the chromosomal aberrationshave a minimum segment size of at least 1 Mb.

69. The method of paragraph 45-68, wherein the chromosomal aberrationshave a minimum segment size of at least 12 Mb.

70. The method of paragraph 45-69, wherein the plurality of chromosomalaberrations comprises at least 5 chromosomal aberrations.

71. The method of paragraph 45-70, wherein the plurality of chromosomalaberrations comprises at least 13 chromosomal aberrations.

72. The method of paragraph 45-71, wherein the chromosomal loci areselected from the group consisting of single nucleotide polymorphisms(SNPs), restriction fragment length polymorphisms (RFLPs), and simpletandem repeats (STRs).

73. The method of paragraph 45-72, wherein the chromosomal loci areanalyzed using at least one technique selected from the group consistingof molecular inversion probe (MIP), single nucleotide polymorphism (SNP)array, in situ hybridization, Southern blotting, transcriptional arrays,array comparative genomic hybridization (aCGH), and next-generationsequencing.

74. The method of paragraph 45-73, wherein outcome of treatment ismeasured by at least one criteria selected from the group consisting ofsurvival until mortality, pathological complete response,semi-quantitative measures of pathologic response, clinical completeremission, clinical partial remission, clinical stable disease,recurrence-free survival, metastasis free survival, disease freesurvival, circulating tumor cell decrease, circulating marker response,and RECIST criteria.

75. The method of paragraph 45-74, further comprising determining asuitable treatment regimen for the subject.

76. The method of paragraph 45-75, wherein said suitable treatmentregimen comprises at least one platinum-based chemotherapeutic agentwhen a plurality of genomic chromosomal aberrations is determined ordoes not comprise at least one platinum-based chemotherapeutic agentwhen no plurality of genomic chromosomal aberrations is determined.

EXAMPLES Example 1: Materials and Methods for Example 2

Pathologic response after neoadjuvant cisplatin therapy in the TNBCcohort was measured using the semi-quantitative Miller-Payne scale asdescribed (Silver et al. (2010) J. Clin. Oncol. 28, 1145-1153; Ogston etal. (2003) Breast 12, 320-327). MIP genotyping was performed asdescribed (Wang et al. (2007) Genome Biol. 8, R246). Allele signalintensity and genotypes from MIP genotyping or public SNP array analyseswere processed by the CRLMM algorithm (Lin et al. (2008) Genome Biol. 9,R63) as implemented in the R package “oligo”. DNA copy number wasdetermined using the R package “AromaAffymetrix” (Bengtsson et al.(2008) Bioinformatics 24, 759-767). Processed genotype data was exportedto dChip (available on the world wide web athttp://biosun1.harvard.edu/complab/dchip/) for major copy proportion(MCP) determination, defined as ratio of major copy number tomajor+minor copy number (Li et al. (2008) Bioinformatics 9, 204). Anestimate of level of normal DNA contamination was made from the genomicMCP curve as described (Li et al. (2008) Bioinformatics 9, 204). Breastor ovarian cases estimated to have 75% or more tumor content wereincluded in analyses. Allelic imbalance (AI) for specific purposes ofsome Examples described herein was defined as MCP>0.7 and regions of AIdefined as more than 10 consecutive probes with AI. Telomeric AI forspecific purposes of some Examples described herein was defined as AIregions that extend to telomere and do not cross the centromere.Association between NtAI,12 and response to cisplatin in TNBC subjectswas estimated by area under curve (AUC) of receiver operatorcharacteristic (ROC) curve; p value is from two-sided Wilcoxon's ranktest. Association between telomeric AI and time to recurrence of ovariancancer after platinum therapy was estimated by Kaplan Meier analysisusing a cutoff of 13 to define high NtAI,12 group; p value is based onlog-rank test. A complete listing of materials and methods is asfollows:

Cell Lines and Drug Sensitivity Assays

Tripe-negative breast cancer cell lines BT20, BT549, HCC1187, HCC38,MDA-MB231 and MDA-MB468 were maintained at 37° C. with 5% CO2 in RPMI1640 medium and/or MEM medium supplemented with 10% FBS or othersupplements as recommended by ATCC for each cell line. To test drugsensitivity, cells were exposed to a series of concentrations ofcisplatin for 48 hours. Viable cell number was quantified usingCellTiter 96 Aqueous One Solution Cell Proliferation Assay according tothe manufacturer's instructions (Promega). The results are presented asthe percentage of viable cells in drug-treated wells vs. media-treatedcontrol wells and plotted as a drug-does dependent cell survival curves(FIG. 1A). Drug sensitivity was quantified as the does of drug causing a50% reduction of growth (IC50). This data was originally generated for aseparate study in which it was reported as “data not shown” in Li et al.(2010) Nat. Med. 16, 214-218.

Breast Cancer Cohort

A total of 28 mainly sporadic TNBC patients were treated with cisplatinmonotherapy in the neo-adjuvant setting (Silver et al. (2010) J. Clin.Oncol. 28, 1145-1153). Cisplatin response was measured using thesemiquantitative Miller-Payne score by pathological assessment ofsurgical samples after therapy (Ogston et al. (2003) Breast 12,320-327). Pathologic complete response is equivalent to Miller-Paynescore and is defined as no residual invasive carcinoma in breast orlymph nodes.

Preparation of Breast Cancer Samples

A frozen core biopsy of the tumor was obtained before treatment started.Tumor tissue was available in the frozen core biopsy for 24 of 28 casesand in formalin fixed paraffin embedded diagnostic core biopsy samplesfrom an additional 3 cases. Tumor cells were enriched by needlemicrodissection to remove stroma from hematoxylin and eosin (H & E)stained tissue sections. The remaining tissue on slides was examined bymicroscopy for estimation of enrichment. DNA was extracted from enrichedtumor cells by proteinase K and RNase A digestions, phenol/chloroformextraction followed by ethanol precipitation. Adequate DNA for MIPgenotyping analysis (minimum 80 ng) was obtained from all 27 cases forwhich tumor tissue was available. Paired normal DNA from each patientwas obtained from peripheral blood lymphocytes.

Molecular Inversion Probe (MIP) Genotyping Analysis

DNA from breast tumor biopsy samples were sent to Affymetrix, Inc.(Santa Clara, Calif.) for MIP targeted genotyping analysis whichgenerated allele signal intensity and genotypes for 42,000 individualsingle nucleotide polymorphisms (SNP). The complete MIP genotype dataset is available on the NCBI GEO database.

Public Datasets

Affymetrix SNP 6.0 genomic profiles of six triple negative breast cancercell lines, BT20, BT549, HCC1187, HCC38, MDA-MB231 and MDA-MB468, wereacquired from the Welcome Trust Sanger Institute (information availableon the world wide web at http://www.sanger.ac.uk/).

SNP data representing 118 ovarian carcinoma tumors arrayed on theAffymetrix 50K XbaI platform were acquired from the gene expressionomnibus (GEO, GSE13813; Etemadmoghadam et al. (2009) Clin. Cancer Res.15, 1417-1427). Of these, 38 tumors were of the serous subtype, hadresidual tumor after surgical debulking of less than 1 cm, and hadreceived either adjuvant cisplatin or carboplatin treatment. Mostpatients (35 of 38) had also received taxane treatment.

Genotype and Copy Number Analysis

Allele signal intensity and genotypes from MIP genotyping or SNP arrayanalyses were processed by the CRLMM algorithm (Lin et al. (2008) GenomeBiol. 9, R63) as implemented in the R package “oligo”. DNA copy numberwas determined using the R package “AromaAffymetrix” (Bengtsson et al.(2008) Bioinformatics 24, 759-767). Processed genotype data was exportedto dChip (available on the world wide web athttp://biosun1.harvard.edu/complab/dchip/) for major copy proportion(MCP) determination.

MCP is defined as the ratio of the major allele copy number to themajor+minor allele copy number (Li et al. (2008) Bioinformatics 9, 204).The degree of normal cell contamination was estimated by the degree ofshift in the MCP curve of the majority of regions showing allelicimbalance across genome, excluding all regions of copy number gain (Theshift observed in the genomic MCP curves in paired normal and tumor cellline mixture experiments was used as reference to estimate normalcontamination as described (Waddell et al. (2009) Breast Cancer Res.Treat. (December 4; e-published)). Accordingly, 21 of the 27 breasttumor samples and 33 of 38 of the ovarian cancer cases were estimated tohave 25% or less of normal DNA contamination (D75% tumor content) andwere deemed acceptable for subsequent analysis.

Allelic imbalance (AI) was defined for purposes of some Examplesdescribed herein as MCP>0.70, which allows detection of the majority ofloss of heterozygosity (LOH) events and of high-copy monoallelicamplifications in samples with 25% or less contamination orheterogeneity, but also excludes low-level copy gains (4-copy gains orless). Regions of AI were defined for purposes of some Examplesdescribed herein as more than 10 consecutive probes showing AI. In theTNBC dataset, the AI regions defined by these criteria included allcallable LOH regions as determined from conventional genotypecomparison. The total copy numbers (combining both alleles) weresegmented by the circular binary segmentation algorithm. Eighty fivepercent of AI regions had total copy number near diploid or below, 9% ofthe AI regions showed total copy gain of 3, and 6% with total copy gain□4. Thus, the identified AI regions predominantly represent LOH oruniparental chromosomal deletion.

Association Between Number of Genomic Aberrations and PlatinumSensitivity In Vitro

The numbers of regions of AI or regions with copy number aberration werecompared to cell line-specific IC50 values after applying a 1 Mb minimumsize filter to remove very small regions that could be caused by noisein the SNP 6.0 data (FIG. 3). For comparison of telomeric andinterstitial AI regions, telomeric AI was defined for purposes of theExamples described herein as AI that extends to the telomere but doesnot cross the centromere. Conversely, interstitial AI was defined forpurposes of the Examples described herein as AI regions that do notinvolve the telomere. To investigate if there was an optimum minimumsize of telomeric AI or copy number alteration segments that showed asuperior correlation to the cisplatin IC50, linear regression was usedto compare the IC50 values with the total number of segments larger thana certain threshold, which was increased by 1 Mb intervals between 0 and100 Mb (FIG. 5).

Association Between Number of Telomeric AI Regions and PlatinumSensitivity in Tumors

Total number of regions of telomeric AI was determined for each TNBCcase with at least 75% tumor content. The optimal minimum telomeric AIsegment size threshold of 12 Mb found in the cell lines were applied,and NtA1,12 were counted for each subject. ROC (Receiver OperatingCharacteristic) curve analysis was performed to evaluate the capabilityof the total number of telomeric AI segments to predict pCR(Miller-Payne score 5) to cisplatin treatment.

The association of NtAI,12 with pCR to cisplatin was estimated by thearea under the curve (AUC); the corresponding p-value is from two-sidedWilcoxon's rank test. Based on the ROC analysis, a NtAI.12 of 13resulted in 100% sensitivity for prediction of pCR in the TNBC cisplatintreated cohort.

The association between NtA1,12 and time to recurrence afterplatinum-based therapy in the ovarian cancer cohort was estimated byKaplan-Meier analysis with the “high NtA1,12” group defined as at least13 regions of NtA1,12. P value is based on a log-rank test.

Example 2: Total Number of Chromosomal Rearrangements is Predictive ofChemotherapeutic Drug Sensitivity

Without being bound by theory, it is believed that intrachromosomal lossof heterozycosity (LOH) or allelic imbalance (AI) results from improperrepair of chromosomal DNA double-strand breaks and that the genome-widecount of these chromosomal rearrangements in a specific tumor mayindicate the degree of DNA repair incompetence, independent of thespecific causative DNA repair defect. Therefore, the total number ofchromosomal rearrangements in a tumor reflects the inability to repairDNA damage induced by drugs like cisplatin, and consequently predictssensitivity to these agents. Cisplatin sensitivity of six TNBC celllines for which SNP array data was available from Wellcome Trust SangerInstitute, UK, was thus determined (FIG. 1A). AI was determined by majorcopy proportion (MCP) analysis, a method less sensitive to normalcontamination in heterogeneous tumor samples (Li et al. (2008)Bioinformatics 9, 204).

The MCP is the number of major copy alleles at a locus divided by thesum of the number of major plus minor copy alleles (FIG. 2). Gains orreductions in total DNA copy number at each chromosomal region wereinferred using dChip software (Lin et al. (2004) Bioinformatics 20,1233-1240).

The DNA repair lesion(s) rendering cells sensitive to cisplatin maypreferentially induce chromosomal alterations of a specific type or witha specific size range. In the six cell lines, the association betweencisplatin sensitivity and each of four measures of chromosomalalterations was tested. The four measures were (1) the number ofchromosome regions with AI (NAI), (2) the number of copy numberaberrations (NCNA), (3) the number of regions with copy number gain, and(4) the number of regions with copy number decrease (FIG. 3). Of thesefour measures, the NAI was most strongly correlated with cisplatinsensitivity (R2=0.5).

Known defects in DNA double strand break repair, including loss of BRCA1or mutations in the Bloom helicase, cause the spontaneous formation oftriradial and quadriradial chromosome structures, which are cytologicindications of aberrant recombination (Silver et al. (2007) Cell 128,991-1002; Luo et al. (2000) Nat. Genet. 26, 424-429; Xu et al. (1999)Mol. Cell 3, 389-395). The resolution of these chromosome rearrangementsat mitosis can result in loss of distal (telomeric) chromosome fragmentsand large regions of AI (Luo et al. (2000) Nat. Genet. 26, 424-429;Vrieling (2001) Nat. Genet. 28, 101-102). Thus, telomeric andinterstitial (non-telomeric) AI regions were compared and it was foundthat the correlation between cisplatin sensitivity and AI was strongerwhen limited to AI regions involving telomeres, whereas only weakassociation was seen between cisplatin sensitivity and the number ofinterstitial AI regions (FIG. 4).

Next, it was determined if the correlations could be improved betweencisplatin sensitivity and measures of genomic aberrations by testing arange of minimum segment sizes, in TNBC cell lines (FIG. 1B and FIGS.5A-5C). Significant correlation with cisplatin sensitivity was seenusing minimum telomeric AI segment size cutoffs between 5 and 25 Mb withthe highest level of correlation seen for total number of segments withtelomeric AI (NtAI) of at least 12 MB (R2=0.8; P=0.016; FIG. 1C).Testing for optimum minimum segment size did not appreciably improve thecorrelation between cisplatin sensitivity and measures of copy numberaberrations, which remained not significant (FIGS. 5D-5F).

Whether the same association between NtAI and cisplatin sensitivity waspresent in clinical tumor samples using the optimum segment size cutoffof 12 MB (NtAI,12) was also investigated. NtAI,12 was compared tochemotherapy response in subjects with TNBC treated with preoperativecisplatin monotherapy (Silver et al. (2010) J. Clin. Oncol. 28,1145-1153). Cryostat tissue sections of pre-treatment core biopsies wereenriched for tumor cells by needle microdissection, and DNA wasextracted for genotyping. Genotypes of 42,000 SNPs were determined withthe Molecular Inversion Probe (MIP) targeted genotyping system(Affymetrix, Inc.) (Wang et al. (2007) Genome Biol. 8, R246). The degreeof normal cell contamination was estimated from the MIP genotype data asdescribed (Li et al. (2008) Bioinformatics 9, 204). No association wasobserved between the degree of normal contamination and response tocisplatin (R2=0.004, P=0.75).

MIP genotype data from 21 cases with at least 75% tumor cell contentwere evaluated by MCP analysis to define the regions of telomeric,interstitial, or whole chromosome AI across the genome (FIG. 6A and FIG.7). A correlation between the NtAI,12 and the response rate wasobserved, as quantified by the Miller-Payne score (R2=0.5; P=0.00032;FIG. 6B; Ogston et al. (2003) Breast 12, 320-327), with higher numbersof tAI regions associated with greater sensitivity to cisplatin.Receiver operating characteristic (ROC) curve analysis revealed thatNtAI,12 was significantly associated with pathologic complete responseto cisplatin (Miller-Payne 5) by the area under the curve (AUC=0.85;P=0.017; FIG. 6C). There was no apparent association between number ofinterstitial AI segments (FIG. 6A) or level of whole chromosome AI (FIG.7) and response to cisplatin.

Serous ovarian carcinoma is often treated with platinum-based therapies.A publicly available SNP array data set of ovarian carcinomas treatedwith cisplatin or carboplatin plus a taxane (Etemadmoghadam et al.(2009) Clin. Cancer Res. 15, 1417-1427) was investigated and 33 cases ofthe serous subtype treated after optimal surgical debulking (residualtumor <1 cm) and reasonable tumor purity (>75%, estimated from SNP data)were identified. NtAI,12 was determined by MCP analysis. In theseplatinum-treated ovarian cancer cases, an association was found betweenhigher levels of telomeric AI in tumors and absence of relapse within ayear (FIG. 8A). The ROC analysis in the TNBC cohort was used to define acutoff value of NtAI,12 of at least 13 events, which gave the greatestsensitivity for the classification of pCR to platinum therapy in theTNBC cohort. This cutoff was used to classify the ovarian cancer cohortinto high and low NtAI,12 groups and longer disease-free survival, asurrogate indicator of higher sensitivity to platinum, was found in thehigh NtAI,12 group (FIG. 8B).

Thus, chromosomal instability, manifested by high levels of telomericAI, characterize subsets of TNBC and ovarian cancer, and further, higherlevels of these changes predict specific therapeutic vulnerabilities.Although sporadic TNBC appear similar to BRCA1-associated breast cancerin the patterns of chromosomal alterations and various otherimmuno-phenotypes and histological features, the precise moleculardefect(s) in maintenance of chromosomal stability in these tumors isunknown. The results of the examples described herein indicate that theburden of chromosome rearrangements resulting from improperly repairedDNA strand breaks are indicators of DNA repair defects that sensitizecells to certain chemotherapies (FIG. 9). As such, levels of allelicimbalance provide an accurate biomarker for predicting tumor sensitivityto treatment with genotoxic agents, irrespective of knowledge of thecausative DNA repair lesion.

Example 3

In this study, we utilized two preoperative clinical trials in womenwith triple negative breast cancer treated with cisplatin, in whichpathologic response at the time of surgery provided an experimentalendpoint. Sporadic triple negative breast cancers are heterogeneous intheir responses to platinum salts, chemotherapeutic agents that dependin part on DNA repair defects for their cytotoxic activity (Sakai, W.,et al. Secondary mutations as a mechanism of cisplatin resistance inBRCA2-mutated cancers. Nature 2008; 451: 1116-1120; Edwards, S. L., etal. Resistance to therapy caused by intragenic deletion in BRCA2. Nature2008; 451: 1111-1115). Lesions in DNA repair caused by BRCA1 or BRCA2dysfunction lead to platinum sensitivity; we reasoned that the types ofchromosomal aberrations arising in the context of BRCA dysfunction mightalso be associated with platinum sensitivity in wtBRCA (wild type BRCA)cancers. Based on results in cell lines, we chose to enumerate one suchchromosomal abnormality, telomeric allelic imbalance (NtAI) inpre-treatment tumor genomes and to relate this to pathologic responseafter cisplatin, an exemplary platinum comprising therapy.

NtAI was associated with response to platinum treatment in our TNBCcisplatin trials and in platinum treated serous ovarian cancer andsuggests the burden of this genomic abnormality exposes an underlyingdeficiency of DNA repair in the platinum-sensitive subset of thesecancers. Allelic imbalance propagated from a given chromosomal locationto the telomere suggests the operation of error-prone processes givingrise to abnormal crossover or template switching events, rather thanerror-free DNA repair.

We found the breakpoints of tAI regions are non-random and enriched forCNVs. This pattern also suggests defective DNA repair. CNVs areassociated with other repeat sequences such as Alu repeats, areconcentrated in pericentromeric and subtelomeric regions, and areassociated also with common fragile sites (McVean, G. What drivesrecombination hotspots to repeat DNA in humans? Philos Trans R Soc LondB Biol Sci 2010; 365: 1213-1218; Puliti, A., et al. Low-copy repeats onchromosome 22q11.2 show replication timing switches, DNA flexibilitypeaks and stress inducible asynchrony, sharing instability features withfragile sites. Mutat Res 2010; 686: 74-83). These repeat elements arethought to result in replication “slow zones” prone to replicationstalling and formation of DNA double strand breaks (Richard, G. F.,Kerrest, A., and Dujon, B. Comparative genomics and molecular dynamicsof DNA repeats in eukaryotes. Microbiol Mol Biol Rev 2008; 72: 686-727;Cha, R. S. and Kleckner, N. ATR homolog Mecl promotes fork progression,thus averting breaks in replication slow zones. Science 2002; 297:602-606). Furthermore, downregulation of Rad51 or inhibition of BRCA1increases the fragility at such sites when cells are under replicationstress (Arlt, M. F., et al., BRCA1 is required for common-fragile-sitestability via its G2/M checkpoint function. Mol Cell Biol 2004; 24:6701-6709; Schwartz, M., et al. Homologous recombination andnonhomologous end-joining repair pathways regulate fragile sitestability. Genes Dev 2005; 19: 2715-2726). The observed association oflow BRCA1 expression levels in many tumors with high NtAI suggestsdeficient homologous recombination, impaired S or G2/M checkpointfunction, or a combination of these factors underlies the generation ofthis type of genomic abnormality.

Cisplatin forms inter-strand crosslinks on DNA that lead to stalledreplication forks and DNA double stand breaks that must be repaired ifthe cell is to survive. It is likely these breaks are repaired usingsimilar mechanisms to those employed at stalled replication forks andDNA breaks generated at sites of CNVs. Therefore, high pre-treatmentNtAI identifies tumors unable to accurately repair breaks and restartstalled replication forks at sites of CNV. These same tumors are alsounable to contend with stalled forks at sites of cisplatin crosslinks.

While allelic imbalance at sites of CNV may reflect inefficienterror-free repair, other explanations should be considered. Both triplenegative cohorts showed a significant relationship between NtAI andpathologic response to cisplatin chemotherapy. Nevertheless, there werepatients in both trials whose tumors showed poor response to cisplatintherapy despite having high NtAI. Similarly, a few of the BRCA1-mutatedovarian cancers had high NtAI yet were resistant to platinum therapy.Since NtAI is a summation of ongoing and past DNA lesions, resistancemechanisms acquired after generation of tAI would confound therelationship between NtAI and response. In carriers of BRCA1 or BRCA2mutations, some tumors that become resistant to platinum agents carry areversion mutation that partially or completely restores BRCA1 or BRCA2function and restores homologous recombination (Sakai, W., et al.Secondary mutations as a mechanism of cisplatin resistance inBRCA2-mutated cancers. Nature 2008; 451: 1116-1120; Edwards, et al.Resistance to therapy caused by intragenic deletion in BRCA2. Nature2008; 451: 1111-1115; Swisher, E. M., et al., Secondary BRCA1 mutationsin BRCA1-mutated ovarian carcinomas with platinum resistance. Cancer Res2008; 68: 2581-2586). Reversion has also been seen in a cell line with aBRCA2 mutation selected for PARP inhibitor resistance (Edwards, et al.Resistance to therapy caused by intragenic deletion in BRCA2. Nature2008; 451: 1111-1115). Reversion mutations and in cis compensatingmutations were observed in Fanconi anemia patients, resulting inimprovement in their bone marrow function (Kalb, R., et al., Fanconianemia: causes and consequences of genetic instability. Genome Dyn 2006;1:218-242). Inactivation of TP53BP1 restores the balance betweenhomologous recombination and non-homologous end joining in BRCA1-mutatedcells and renders them resistant to PARP inhibitors (Bouwman, P., et al.53BP1 loss rescues BRCA1 deficiency and is associated withtriple-negative and BRCA-mutated breast cancers. Nat Struct Mol Biol2010; 17: 688-695; Bunting, S. F., et al. 53BP1 inhibits homologousrecombination in Brca1-deficient cells by blocking resection of DNAbreaks. Cell 2010; 141: 243-254). Finally, drug transporters may preventaccumulation of platinum agents in tumor cells (Burger, H., et al., Drugtransporters of platinum-based anticancer agents and their clinicalsignificance. Drug Resist Updat 2011). Therefore, reversion of orcompensation for a preexisting DNA repair defect may generate a tumorwith high NtAI but resistance to platinum treatment; other platinumresistance mechanisms unrelated to DNA repair would have the sameeffect.

Our analysis suggests an outline of the molecular taxonomy of TNBC andovarian cancer with respect to DNA repair and drug sensitivity. Mostplatinum resistant breast or ovarian cancers are tumors with repairproficiency and low NtAI. Two subsets of wtBRCA tumors possess high NtAIand are sensitive to platinum-containing drugs. In one of these subsets,repair deficiency may be the consequence of low BRCA1 expression and inthe other subset, repair may be crippled by mechanisms that do notdepend upon BRCA1 expression. These observations will no doubt befurther refined; inclusion of reversion mutations, compensations byother events in DNA repair pathways, other mechanisms of drugresistance, and other as yet unappreciated factors may help to enhanceour prediction of drug sensitivity in the future.

In conclusion, a summary measure of telomeric chromosome aberrations inthe tumor genome, NtAI, predicts sensitivity to platinum treatment. Ourfindings implicate NtAI as a marker of impaired DNA double-strand breakrepair. Assays to determine NtAI are feasible using formalin fixedparaffin embedded tumor material and recent algorithms such as ASCATpermit accurate determination of copy number and allelic imbalance in amajority of samples despite low tumor cell content. NtAI may proveuseful in predicting response to a variety of therapeutic strategiesexploiting defective DNA repair.

Materials and Methods

Cell lines and drug sensitivity assays: Drug sensitivity measurements inbreast cancer cell lines BT20, BT549, HCC1187, HCC1143, MDA-MB-231,MDA-MB-468, HCC38, MDA-MB-453 (triple negative), CAMA-1, MCF7, T47D (ERpositive), BT474, HCC1954 and MDA-MB-361 (HER2positive) was originallygenerated for a separate study in which it was reported as “data notshown” in a recently published manuscript (Li, Y., et al. Amplificationof LAPTM4B and YWHAZ contributes to chemotherapy resistance andrecurrence of breast cancer. Nat Med 2010; 16: 214-218). Briefly, cellswere exposed to a series of concentrations of various chemotherapeuticagents for 48 hours. Viable cell number was quantified using CellTiter96 AQueous One Solution Cell Proliferation Assay according to themanufacturer's instructions (Promega). Drug sensitivity was quantifiedas the dose of drug resulting in a 50% reduction of growth (IC50). Wefound MCF7 to be highly resistant to all of the chemotherapeutic agentstested, consistent with its reported caspase-3 deficiency and resistanceto drug induced apoptosis (Yang, X. H., et al., Reconstitution ofcaspase 3 sensitizes MCF-7 breast cancer cells to doxorubicin- andetoposide-induced apoptosis. Cancer Res 2001; 61: 348-354). In ouranalyses with measures of genomic aberration, MCF7 was the only clearoutlier and for these reasons, was excluded from our analyses.

Breast Cancer Cohorts and Assessment of Therapeutic Response

For this study, subjects were included for analysis of response tocisplatin if they progressed on therapy or if they received at least 3of 4 cycles of the planned cisplatin therapy, had received no othernon-protocol therapy before surgery, and if an adequate amount of tumorwas available from the pre-treatment biopsy. Therapeutic response wasmeasured using the semiquantitative Miller-Payne grading system, whichestimates the percent reduction in invasive tumor volume and cellularitybased on pathological assessment of surgical samples after therapy(Ogston, K. N., et al., A new histological grading system to assessresponse of breastcancers to primary chemotherapy: prognosticsignificance and survival. Breast 2003; 12: 320-327). Cisplatin-1consists of 28 mainly sporadic TNBC patients treated with preoperativecisplatin monotherapy, of whom 4 progressed on therapy and 24 completed4 cycles of cisplatin therapy (Silver, D. P., et al. Efficacy ofneoadjuvant Cisplatin in triple-negative breast cancer. J Clin Oncol2010; 28: 1145-1153). Cisplatin-2 consists of 51 TNBC patients treatedwith preoperative cisplatin and bevacizumab, of which one patientprogressed on therapy and 44 patients completed 4 cycles of cisplatintherapy prior to surgery (Ryan, P. D., et al. Neoadjuvant cisplatin andbevacizumab in triple negative breast cancer (TNBC): Safety andEfficacy. J Clin Oncol 2009; 27: 551). Two patients included in thisstudy were taken to surgery after completing 3 cycles of cisplatintherapy due to the development of toxicity; in both cases there was noappreciable pathologic response in the excised tumor after 3 cycles ofcisplatin.

Preparation of Breast Cancer Samples

For both trials, core biopsies of tumor were obtained before initiationof treatment. Adequate tumor for analysis was present for 27 of 28subjects in Cisplatin-1 and 37 of 51 subjects in Cisplatin-2. H&Estained tissue sections of pre-treatment core needle biopsies wereexamined microscopically; for all biopsies for which enrichment wasdeemed feasible, sections were manually microdissected using an 18-gaugeneedle. DNA was extracted by proteinase K and RNase A digestions,phenol/chloroform extraction, and ethanol precipitation. Paired normalDNA from patients was obtained from peripheral blood lymphocytes for allcases in Cisplatin-1 and from 10 cases in Cisplatin-2.

TCGA Ovarian and Breast Cancer Cohorts

Public SNP array data, expression data, and clinical annotation data wasobtained for the TCGA ovarian (Bell, D., et al., Integrated genomicanalyses of ovarian carcinoma. Nature 2011; 474: 609-615) and breastcancer cohorts from the TCGA web site(http://tcga-data.nci.nih.gov/tcga/). BRCA1 and BRCA2 mutation statusfor the ovarian cancers was obtained from cBIO data portal(http://bit.ly/wpwRXd). In the ovarian cohort, we identified 218 sampleswith SNP data that passed ASCAT, BRCA mutation status, and interpretableclinical annotations for treatment and outcomes indicating initialtreatment with adjuvant platinum-based chemotherapy, predominantly thecombination of carboplatin and docetaxel. We classified “treatmentsensitive” as those annotated as partial or complete response to initialtreatment and no progression or recurrence within 6 months of initialtreatment (n=187); “treatment resistant” were those annotated as stableor progressive disease on initial therapy or disease recurrence orprogression within 6 months (n=31). In the breast cohort, we identified78 samples with matched gene expression and SNP data that passed ASCAT,which were classified as ER−/HER2− based on clustering of the ESR1 andERBB2 gene (see supplementary methods).

Genotyping and Copy Number Analysis

DNA was sent to Affymetrix, Inc. (Santa Clara, Calif.) for determinationof genotypes using the molecular inversion probe based genotypingsystem, OncoScan FFPE Express (Wang, Y., et al. Analysis of molecularinversion probe performance for allele copy number determination. GenomeBiol 2007; 8: R246). The commercial assay, which determines genotype of330,000 SNPs was used for analysis of the Cisplatin-2 trial. An earlyversion of the OncoScan assay which genotypes 42,000 SNPs was used forthe Cisplatin-1 trial. Allele signal intensity and genotypes from theOncoScan genotyping assay were processed and provided to us byAffymetrix. The OncoScan SNP genotype data for the cisplatin therapytrials is submitted to the NCBI GEO database under accession GSE28330.Public SNP array raw data for the breast cancer cell lines were obtainedfrom the Sanger Institute Catalogue Of Somatic Mutations In Cancer website, world wide web “dot” sanger “dot” ac “dot” uk/cosmic (Bamford, S.,et al. The COSMIC (Catalogue of Somatic Mutations in Cancer) databaseand website. Br J Cancer 2004; 91: 355-358), public SNP array data froman independent breast cancer cell line study, Heiser et al. (Heiser, L.M., et al. Subtype and pathway specific responses to anticancercompounds in breast cancer. Proc Natl Acad Sci USA 2011), and public SNParray data from the TCGA ovarian (Bell, D., et al., Integrated genomicanalyses of ovarian carcinoma. Nature 2011; 474: 609-615) and breastcancer cohorts were preprocessed by the AROMAv2 and CalMaTe algorithms(Bengtsson, H., Wirapati, P., and Speed, T. P. A single-arraypreprocessing method for estimating full-resolution raw copy numbersfrom all Affymetrix genotyping arrays including GenomeWideSNP 5 & 6.Bioinformatics 2009; 25: 2149-2156) and, when a paired normal sampleswas available, TumorBoost (Bengtsson, H., Neuvial, P., and Speed, T. P.TumorBoost: normalization of allele-specific tumor copy numbers from asingle pair of tumor-normal genotyping microarrays. BMC Bioinformatics2010; 11: 245). Processed genotype data from OncoScan genotyping andpublic SNP array data was analyzed for allele-specific copy numbers andtumor cell content by the algorithm “Allele-specific copy numberanalysis of tumors”, ASCAT (Van Loo, P., et al. Allele-specific copynumber analysis of tumors. Proc Natl Acad Sci USA 2010; 107:16910-16915). ASCAT is designed to correct for normal cell contaminationand tumor cell ploidy, but occasionally fails to fit a model to a givensample. In this study, ASCAT failed to process 3 of 14 cell lines fromSanger, 15 of 42 cell lines from Heiser et al., and 5 of 37 samples fromthe Cisplatin-2 trial. Allelic imbalance was defined as any time thecopy number of the two alleles were not equal, and at least one allelewas present (FIG. 16). To ensure that all trial cases were comparable,we eliminated cases estimated by ASCAT to have less than 36% tumor cellcontent, the highest level of normal cell admixture in the Cisplatin-1trial, which was the trial with an overall greater tumor purity. Thus weincluded all 27 samples with SNP array data from the Cisplatin-1 trial,26 out of 32 samples with SNP array data that passed ASCAT from theCisplatin-2 trial.

A minimum number of consecutive probes showing an aberration wasrequired in order to call regions of AI and CNA with confidence. Toensure similar aberration detection across the three platforms that wereused, the minimum number of probes required to define a region ofaberration was set to be proportional to the overall SNP density of theplatform. The probe densities of the platforms were 42,000/genomeOncoScan (prototype), 330,000/genome OncoScan FFPE Express, and900,000/genome SNP6.0 for an approximate ratio of 1:8:20. Minimum proberequirements of 25 probes for 42 k OncoScan prototype, 200 probes for330 k OncoScan FFPE Express, and 500 probes for SNP6.0 platform werechosen based on optimizing for correlation of aberration measurement ina subset of samples with replicate data generated on both versions ofthe OncoScan platform (See also Supplementary Methods).

Telomeric AI and telomeric CNA are defined as regions that extend to oneof the sub-telomeres but do not cross the centromere. Copy number oftelomeric AI regions was defined as the mean copy number of the probesmapping to the region. Copy loss was defined as a mean of less than 1.5copies and copy gain was defined as a mean of greater than 2.5 copies.Association between NtAI and response to cisplatin in the TNBC clinicaltrials was measured by the AUC of the ROC curve for binary response.Statistical significance was assessed by Wilcoxon's rank sum test. All Pvalues are two-sided.

Enrichment of Copy Number Variants at Site of DNA Breakpoints

The genomic location of common copy number variants (CNVs) was acquiredfrom the Database of Genomic Variants(http://projects.tcag.ca/variation/). Mapping for HG17 and HG18 wasacquired in order to match the SNP probe mapping of the 42K prototypeand 330K commercial OncoScan platforms, respectively. CNVs wereconsidered associated with a breakpoint if they overlapped within a 25kb window on either side of the breakpoint. To test for enrichment, weperformed 1000 permutations for each cohort, where we randomly shuffledthe location of the DNA breakpoints based on the location of the SNPprobes, and determined how many were associated with CNVs.

BRCA1 Transcript Quantitation and Promoter Methylation Analysis

BRCA1 exon 16/17 and RPLP0 (control) quantitative polymerase chainreaction assay was performed as previously described (Silver, D. P., etal. Efficacy of neoadjuvant Cisplatin in triple-negative breast cancer.J Clin Oncol 2010; 28: 1145-1153) using amplified tumor cDNA generatedusing Ovation RNA Amplification System V2 kit (NuGen Technologies, Inc.,San Carlos, Calif.). BRCA1 promoter methylation assay was performed aspreviously described (Silver, D. P., et al. Efficacy of neoadjuvantCisplatin in triple-negative breast cancer. J Clin Oncol 2010; 28:1145-1153).

BRCA1 Expression in Public TCGA Cohorts.

Public normalized and summarized Agilent based gene expression data wasacquired from the TCGA for all breast cancer samples (level 3). RawAffymetrix CEL files were obtained for ovarian cancer samples (level 1).Expression data for all TCGA ovarian cancer samples were normalized andsummarized using RMA, and the probe set “204531_s_at” was identified asthe optimum probe set for measuring BRCA1 expression using the R package“JetSet” (Li, Q., et al., Jetset: selecting the optimal microarray probeset to represent a gene. BMC Bioinformatics 2011; 12: 474).

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thespecification, including the examples, are hereby incorporated byreference in their entirety as if each individual publication, patent orpatent application was specifically and individually indicated to beincorporated by reference. In case of conflict, the present application,including any definitions herein, will control.

Also incorporated by reference in their entirety are any polynucleotideand polypeptide sequences which reference an accession numbercorrelating to an entry in a public database, such as those maintainedby The Institute for Genomic Research (TIGR) on the world wide weband/or the National Center for Biotechnology Information (NCBI) on theworld wide web.

EQUIVALENTS

Those skilled in the art will recognize, or be able to ascertain usingno more than routine experimentation, many equivalents to the specificembodiments of the invention described herein. Such equivalents areintended to be encompassed by the following paragraphs.

1.-8. (canceled)
 9. A method of administering an anti-cancer treatmentto a human patient, the method comprising: (1) directing a clinicallaboratory to (a) detect a plurality of chromosomal aberrations inchromosomal segments comprising a plurality of loci in a sample from ahuman patient, wherein chromosomal aberrations are detected in at leastone pair of human chromosomes of a cancer cell of the patient, whereineach of the chromosomal segments is at least 12 Mb in length, extends toand involves the telomere but does not cross the centromere, (b)calculate a telomeric imbalance score (NtAI) by summing the number ofchromosomal aberrations detected in step (a), and (c) communicate anNtAI to a clinician, and (2) administering an anti-cancer therapyselected from the group consisting of platinum-comprising therapy, DNAdamaging agent comprising therapy, anthracycline-comprising therapy,topoisomerase I inhibitor-comprising therapy and PARP inhibitorcomprising therapy to the patient in whose sample an NtAI of at least 8is detected.
 10. The method of claim 9, wherein said detecting aplurality of chromosomal aberrations is in at least two, five, ten or 21pairs of human chromosomes.
 11. The method of claim 9, wherein the DNAdamaging agent is cisplatin, carboplatin, oxalaplatin, or picoplatin,said anthracycline is epirubincin or doxorubicin, said topoisomerase Iinhibitor is campothecin, topotecan, or irinotecan, and/or said PARPinhibitor is iniparib, olaparib or velapirib.
 12. The method of claim 9,wherein the cancer is selected from the group consisting of breastcancer, ovarian cancer, melanoma, transitional cell bladder cancer,bronchogenic lung cancer, thyroid cancer, pancreatic cancer, prostatecancer, uterine cancer, testicular cancer, gastric cancer, soft tissueand osteogenic sarcomas, neuroblastoma, Wilms' tumor, malignant lymphoma(Hodgkin's and non-Hodgkin's), acute myeloblastic leukemia, acutelymphoblastic leukemia, Kaposi's sarcoma, Ewing's tumor, refractorymultiple myeloma, and squamous cell carcinomas of the head, neck,cervix, colon cancer, or vagina.
 13. A method of administering ananti-cancer treatment to a human patient, the method comprising: (1)receiving a telomeric imbalance score (NtAI) of at least 8 from aclinical laboratory, wherein the NtAI is determined by the steps of: (a)detecting a plurality of chromosomal aberrations in chromosomal segmentscomprising a plurality of loci in a sample from a human patient, whereinchromosomal aberrations are detected in at least one pair of humanchromosomes of a cancer cell of the patient, wherein each of thechromosomal segments is at least 12 Mb in length, extends to andinvolves the telomere but does not cross the centromere, and (b)calculating the NtAI score by summing the number of chromosomalaberrations detected in step (a), and (2) administering to said patientan anti-cancer therapy selected from the group consisting ofplatinum-comprising therapy, DNA damaging agent comprising therapy,anthracycline-comprising therapy, topoisomerase I inhibitor-comprisingtherapy and PARP inhibitor comprising therapy.
 14. The method of claim13, wherein said detecting a plurality of chromosomal aberrations is inat least two, five, ten or 21 pairs of human chromosomes.
 15. The methodof claim 13, wherein the DNA damaging agent is cisplatin, carboplatin,oxalaplatin, or picoplatin, said anthracycline is epirubincin ordoxorubicin, said topoisomerase I inhibitor is campothecin, topotecan,or irinotecan, and/or said PARP inhibitor is iniparib, olaparib orvelapirib.
 16. The method of claim 13, wherein the cancer is selectedfrom the group consisting of breast cancer, ovarian cancer, melanoma,transitional cell bladder cancer, bronchogenic lung cancer, thyroidcancer, pancreatic cancer, prostate cancer, uterine cancer, testicularcancer, gastric cancer, soft tissue and osteogenic sarcomas,neuroblastoma, Wilms' tumor, malignant lymphoma (Hodgkin's andnon-Hodgkin's), acute myeloblastic leukemia, acute lymphoblasticleukemia, Kaposi's sarcoma, Ewing's tumor, refractory multiple myeloma,and squamous cell carcinomas of the head, neck, cervix, colon cancer, orvagina.
 17. A method for selecting platinum-comprising therapy or poly(ADP-ribose) polymerase (PARP) inhibitor therapy for a human subjecthaving cancer comprising: (1) assaying a cancer cell-comprising samplefrom the subject having cancer for telomeric allelic imbalance (tAI),and detecting the number of tAIs (NtAI); and (2) assaying the same or adifferent cancer cell-comprising sample from the subject for mutation(s)in at least one BRCA gene, wherein a platinum-comprising therapy or PARPinhibitor is selected for the subject when the NtAIs is above areference value and/or when a mutation(s) is/are detected in the atleast one BRCA gene.
 18. The method of claim 17, wherein the BRCA geneis BRCA1 and/or BRCA2.
 19. The method of claim 17, wherein themutation(s) in the at least one BRCA1 gene is/are detected by measuring(i) DNA sequencing, and/or (ii) quantitative PCR, and/or (iii)microarray.
 20. The method of claim 17, wherein anon-platinum-comprising therapy is selected for the subject when theNtAI is below the reference level and no mutation is detected in the atleast one BRCA gene.
 21. The method of claim 17, wherein the NtAIreference value is at least 20, 22, 24, or
 27. 22. The method of claim17, further comprising a step of isolating nucleic acids from the cancercell-comprising sample.
 23. The method of claim 17, wherein the canceris selected from breast cancer, ovarian cancer, liver cancer, esophagealcancer, lung cancer, head and neck cancer, prostate cancer, coloncancer, rectal cancer, colorectal cancer and/or pancreatic cancer. 24.The method of claim 17, wherein steps (1) and (2) are performedsimultaneously.
 25. The method of claim 17, wherein steps (1) and (2)are performed in any order.
 26. The method of claim 17, wherein theplatinum comprising therapy is cisplatin, carboplatin, oxaliplatin,nedaplatin, or iproplatin.
 27. The method of claim 17, wherein the PARPinhibitor is olaparib or velaparib.